659 Drift Jobs

Job Description Overview We are seeking a skilled Associate Manager – AIOps & MLOps Operations to support and enhance the automation, scalability, and reliability of AI/ML operations across the enterprise. This role requires a solid understanding of AI-driven observability, machine learning pipeline automation, cloud-based AI/ML platforms, and operational excellence. The ideal candidate will assist in deploying AI/ML models, ensuring continuous monitoring, and implementing self-healing automation to improve system performance, minimize downtime, and enhance decision-making with real-time AI-driven insights. Support and maintain AIOps and MLOps programs, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. Assist in implementing real-time data observability, monitoring, and automation frameworks to enhance data reliability, quality, and operational efficiency. Contribute to developing governance models and execution roadmaps to drive efficiency across data platforms, including Azure, AWS, GCP, and on-prem environments. Ensure seamless integration of CI/CD pipelines, data pipeline automation, and self-healing capabilities across the enterprise. Collaborate with cross-functional teams to support the development and enhancement of next-generation Data & Analytics (D&A) platforms. Assist in managing the people, processes, and technology involved in sustaining Data & Analytics platforms, driving operational excellence and continuous improvement. Support Data & Analytics Technology Transformations by ensuring proactive issue identification and the automation of self-healing capabilities across the PepsiCo Data Estate. Responsibilities Support the implementation of AIOps strategies for automating IT operations using Azure Monitor, Azure Log Analytics, and AI-driven alerting. Assist in deploying Azure-based observability solutions (Azure Monitor, Application Insights, Azure Synapse for log analytics, and Azure Data Explorer) to enhance real-time system performance monitoring. Enable AI-driven anomaly detection and root cause analysis (RCA) by collaborating with data science teams using Azure Machine Learning (Azure ML) and AI-powered log analytics. Contribute to developing self-healing and auto-remediation mechanisms using Azure Logic Apps, Azure Functions, and Power Automate to proactively resolve system issues. Support ML lifecycle automation using Azure ML, Azure DevOps, and Azure Pipelines for CI/CD of ML models. Assist in deploying scalable ML models with Azure Kubernetes Service (AKS), Azure Machine Learning Compute, and Azure Container Instances. Automate feature engineering, model versioning, and drift detection using Azure ML Pipelines and MLflow. Optimize ML workflows with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for data preparation and ETL/ELT automation. Implement basic monitoring and explainability for ML models using Azure Responsible AI Dashboard and InterpretML. Collaborate with Data Science, DevOps, CloudOps, and SRE teams to align AIOps/MLOps strategies with enterprise IT goals. Work closely with business stakeholders and IT leadership to implement AI-driven insights and automation to enhance operational decision-making. Track and report AI/ML operational KPIs, such as model accuracy, latency, and infrastructure efficiency. Assist in coordinating with cross-functional teams to maintain system performance and ensure operational resilience. Support the implementation of AI ethics, bias mitigation, and responsible AI practices using Azure Responsible AI Toolkits. Ensure adherence to Azure Information Protection (AIP), Role-Based Access Control (RBAC), and data security policies. Assist in developing risk management strategies for AI-driven operational automation in Azure environments. Prepare and present program updates, risk assessments, and AIOps/MLOps maturity progress to stakeholders as needed. Support efforts to attract and build a diverse, high-performing team to meet current and future business objectives. Help remove barriers to agility and enable the team to adapt quickly to shifting priorities without losing productivity. Contribute to developing the appropriate organizational structure, resource plans, and culture to support business goals. Leverage technical and operational expertise in cloud and high-performance computing to understand business requirements and earn trust with stakeholders. Qualifications 5+ years of technology work experience in a global organization, preferably in CPG or a similar industry. 5+ years of experience in the Data & Analytics field, with exposure to AI/ML operations and cloud-based platforms. 5+ years of experience working within cross-functional IT or data operations teams. 2+ years of experience in a leadership or team coordination role within an operational or support environment. Experience in AI/ML pipeline operations, observability, and automation across platforms such as Azure, AWS, and GCP. Excellent Communication: Ability to convey technical concepts to diverse audiences and empathize with stakeholders while maintaining confidence. Customer-Centric Approach: Strong focus on delivering the right customer experience by advocating for customer needs and ensuring issue resolution. Problem Ownership & Accountability: Proactive mindset to take ownership, drive outcomes, and ensure customer satisfaction. Growth Mindset: Willingness and ability to adapt and learn new technologies and methodologies in a fast-paced, evolving environment. Operational Excellence: Experience in managing and improving large-scale operational services with a focus on scalability and reliability. Site Reliability & Automation: Understanding of SRE principles, automated remediation, and operational efficiencies. Cross-Functional Collaboration: Ability to build strong relationships with internal and external stakeholders through trust and collaboration. Familiarity with CI/CD processes, data pipeline management, and self-healing automation frameworks. Strong understanding of data acquisition, data catalogs, data standards, and data management tools. Knowledge of master data management concepts, data governance, and analytics.

About Us: MatchMove is a leading embedded finance platform that empowers businesses to embed financial services into their applications. We provide innovative solutions across payments, banking-as-a-service, and spend/send management, enabling our clients to drive growth and enhance customer experiences. Are You The One? As a Technical Lead Engineer - Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to: Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements: At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum. Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale. Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. MatchMove Culture: We cultivate a dynamic and innovative culture that fuels growth, creativity, and collaboration. Our fast-paced fintech environment thrives on adaptability, agility, and open communication. We focus on employee development, supporting continuous learning and growth through training programs, learning on the job and mentorship. We encourage speaking up, sharing ideas, and taking ownership. Embracing diversity, our team spans across Asia, fostering a rich exchange of perspectives and experiences. Together, we harness the power of fintech and e-commerce to make a meaningful impact on people's lives. Personal Data Protection Act: By submitting your application for this job, you are authorizing MatchMove to: collect and use your personal data, and to disclose such data to any third party with whom MatchMove or any of its related corporation has service arrangements, in each case for all purposes in connection with your job application, and employment with MatchMove; and retain your personal data for one year for consideration of future job opportunities (where applicable).

Everything we do is for our customers! Featured on Deloitte's Technology Fast 500 list and G2's leaderboard, Maropost offers a unified commerce experience that our customers need, transforming ecommerce, retail, marketing automation, merchandising, helpdesk and AI operations with one platform designed to scale for fast-growing businesses. With a relentless focus on our customers’ success, we are motivated by customer obsession, extreme urgency, excellence and resourcefulness to to power 5,000+ global brands while we head to 100,000+. Driven by the same customer-centric mentality as above, we empower businesses to achieve their goals and grow alongside us. If you're a driver and not passenger and are ready to make a significant impact and be part of our transformative journey, Maropost is the place for you. The Opportunity Thrive on change and grow beyond limits! We are looking for a bold thinker who sees a chance to learn and define what's possible with every challenge! Ready to make an impact? Welcome to Maropost and you can turn ideas into action! We are seeking a Senior HubSpot Specialist to lead the implementation, optimization, and management of our HubSpot ecosystem. This role will ensure seamless integration with our sales, marketing, and customer success systems and help drive data accuracy, automation, and scalable processes across the organization. What You'll Be Responsible For Own end-to-end management of HubSpot platform including onboarding new teams, setting up workflows, custom properties, and lead scoring models. Partner with RevOps and cross-functional teams to ensure HubSpot is aligned with business processes and reporting needs. Manage user roles, permissions, data hygiene, and system audits. Optimize lead lifecycle management, MQL/SQL handoffs, and routing rules for speed and accuracy. Develop templates, forms, sequences, and CTAs in coordination with content and sales teams. Support the creation of customer journeys to support customer growth and retention. Implement AI functionality available in HubSpot. Maintain data integrity and ensure consistent data syncing between HubSpot and other systems like Salesforce, Clearbit, Segment, or custom APIs. Identify gaps and troubleshoot integration issues. Build custom dashboards and reports to track marketing and sales performance, funnel metrics, and campaign effectiveness and revenue performance. Support quarterly business reviews and performance analytics. Train marketing and sales teams on HubSpot best practices and new features. Create and maintain detailed documentation of system configurations, processes, and governance policies. What You’ll Bring to Maropost 5+ years of experience working in HubSpot (Marketing Hub, Sales Hub, Service Hub). Proven track record in implementing and managing HubSpot for a SaaS business. Strong understanding of lead management, marketing automation, and data workflows. Experience with third-party tools like Zapier, Segment, or Drift is a plus. Analytical mindset with strong Excel/Google Sheets and dashboarding skills. HubSpot certifications (e.g., Marketing Hub Implementation, Revenue Operations) are a strong plus. Excellent communication and project management skills. You exemplify Maropost’s Values: Customer Obsessed Extreme Urgency Excellence Resourceful Message from the Founders: Maropost is looking for builders - people who want to drive our business forward at all costs in order to achieve the goals we have both short and long term for the results and outcomes that that will bring to us all. If that isn't for you that’s ok, for those of you that it is please get in touch with us!

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibility: Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field Experience in Data analysis, Data reasoning, Data Science, or a similar role Programming skills in SQL, Snowflake, Python with experience in pandas, numpy Good understanding of logical reasoning, mathematical and statistical concepts Proven excellent problem-solving and analytical thinking skills Solid communication and collaboration skills to work effectively in a team environment Preferred Qualifications: Experience with the deep data analysis, understanding data and ability to generate insights, full life cycle of AI/ML projects, including EDA, model development, tuning, and drift analysis Familiarity with the US Healthcare domain Familiarity with cloud technologies At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Location : Remote / Gurgaon Engagement : Project-Based | Milestone-Linked Payment Company : OneOrg.ai – Superbrain of Modern Organizations by OriginBluy The Opportunity At OneOrg.ai, we’re expanding our AI Superbrain into pharma manufacturing — where digitization is no longer a future plan, but a regulatory and business imperative. From visual inspections to batch deviations, every manufacturing plant is full of structured data, hidden patterns, and manual inefficiencies . We’re looking for a highly experienced, project-based consultant who can convert this opportunity into AI-powered success stories — one client at a time. Your Role: Project Lead, Not a Lifelong Advisor You’ll lead short-cycle projects that deliver visible value in manufacturing: Identify high-impact AI use cases across GMP, quality control, and production (e.g., visual deviation detection, batch yield variance, SOP non-compliance) Define and scope sharp, implementation-ready pilot proposals Partner with the OneOrg.ai product + tech team to execute each pilot Work with client teams on-ground to ensure adoption, testing, and results Ensure alignment with FDA, WHO-GMP, and CDSCO standards throughout Exit the project once success is achieved — leaving behind a usable, scalable AI asset Ideal Profile 8–15 years in pharma manufacturing, QA/QC, or GMP automation Deep exposure to GMP documentation, audit trails, batch monitoring, and deviations Proven experience in FDA-inspected environments or India GMP-compliant plants Deep familiarity with batch records, deviation analysis, OOS/OOT , and audit trails Prior exposure to computer vision or AI-based inspection tools is highly desirable Strong consulting mindset — can define value, navigate client ops, and close fast Comfortable working in a hands-on, lean, outcome-driven tech environment Project Scope & Payment You will be paid per project , based on defined milestones (Use Case → Pilot → Success → Exit) Option for long-term or repeat engagements if pilots succeed Bonus for successful enterprise conversion (pilot to paid deal) Why This Role Is Different You own the project — define, drive, deliver, exit Your impact is measurable — not strategy decks, but working pilots You’ll work with a real product team (not services or BPO), shaping how AI enters shop floors Be part of building India’s first AI brain for pharma manufacturing Sample Use Cases to Explore Visual Inspection of blister packs using computer vision Batch Deviation Risk Prediction using historical BMR data GMP Document Intelligence – auto-tagging, risk flagging, SOP drift alerts Operator Behavior Detection – camera-based compliance monitoring

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibility Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field Experience in Data analysis, Data reasoning, Data Science, or a similar role Programming skills in SQL, Snowflake, Python with experience in pandas, numpy Good understanding of logical reasoning, mathematical and statistical concepts Proven excellent problem-solving and analytical thinking skills Solid communication and collaboration skills to work effectively in a team environment Preferred Qualifications Experience with the deep data analysis, understanding data and ability to generate insights, full life cycle of AI/ML projects, including EDA, model development, tuning, and drift analysis Familiarity with the US Healthcare domain Familiarity with cloud technologies At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Analytics 1) Purpose of the role We seek a highly skilled Senior Machine Learning Engineer / Senior Data Scientist to design, develop, and deploy advanced machine learning models and systems. The ideal candidate will have deep expertise in machine learning algorithms, data processing, and model deployment, with a proven track record of delivering scalable AI solutions in production environments. This role requires strong technical leadership, collaboration with cross-functional teams, and a passion for solving complex problems. 2) Key tasks & accountabilities Model Development: Design, develop, and optimize machine learning models for various applications, including but not limited to natural language processing, computer vision, and predictive analytics. Data Pipeline Management: Build and maintain robust data pipelines for preprocessing, feature engineering, and data augmentation to support model training and evaluation. Model Deployment: Deploy machine learning models into production environments, ensuring scalability, reliability, and performance using tools like Docker, Kubernetes, or cloud platforms preferably Azure. Research and Innovation: Stay updated on the latest advancements in machine learning and AI, incorporating state-of-the-art techniques into projects to improve performance and efficiency. Collaboration: Work closely with data scientists, software engineers, product managers, and other stakeholders to translate business requirements into technical solutions. Performance Optimization: Monitor and optimize model performance, addressing issues like model drift, bias, and scalability challenges. Code Quality: Write clean, maintainable, and well-documented code, adhering to best practices for software development and version control (e.g., Git). Mentorship: Provide technical guidance and mentorship to junior engineers, fostering a culture of learning and innovation within the team. 3) Qualifications, Experience, Skills Level of educational attainment required Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. PhD is a plus. Previous work experience 5+ years of experience in machine learning, data science, or a related field. Proven experience in designing, training, and deploying machine learning models in production. Hands-on experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Technical Skills required Proficiency in Python and libraries/frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face. Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning, reinforcement learning, optimization). Experience with big data technologies (e.g., Hadoop, Spark, or similar) and data processing pipelines. Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD for ML workflows. Knowledge of software engineering principles, including object-oriented programming, API development, and microservices architecture. Other Skills required Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in a fast-paced, dynamic environment and manage multiple priorities. Experience with generative AI models or large language models (LLMs). Familiarity with distributed computing or high-performance computing environments. And above all of this, an undying love for beer! We dream big to create future with more cheers

Job Description Summary In the business context, coordinate the LV technical studies of the projects. Position in direct contact with customers, develop strong relationships with customers and play the role of interface between GE and customers; explain the technical elements to the other speakers Job Description Roles and Responsibilities: Study the LV specifications and transcribe them into the LV Technical Definition Inform / Alert the PM of difficulties / risks on the LV part Define the technical solutions to meet the specifications (electrical principles, interlocks, etc.). In the event of strong contractual constraints, make sure to propose / argue our standard or managed options in relation to customer specificities and have them approved Define the lists of LV tools and the list of spare parts sold to the customer for after-sales service Manage the production / update of the contractual LV diagrams (to respond to the solutions above) by the LV project technician(s) assigned to it. In the event of subcontracting, monitor and verify the costs with the subcontractors and have the purchase request processed Check the quality of the electrical diagrams and other LV documents produced by the LV project technician(s) (internal or subcontracted) Ensure that the delivery times of the contractual LV plans are met Manage the production / update of the LV plans / specifications necessary for the order of LCCs, cables and cabling equipment from suppliers Ensure delivery deadlines for LV plans for manufacturing and deadlines for launching nomenclatures in the CAPM are met In case of QCD drift, escalate the problems by explaining the impacts on the project (create the associated FME / FMF) He communicates with the supply department by transmitting the technical file for the production of the cabinets. It processes changes and can participate in FAT. It supports the on-site supervisor for the installation of low voltage cabinets. He is responsible for the realization of the "As-Built" plans He will be responsible for creating interfacing cable routing diagrams for GIS LVCC using the CREO tool. Additionally, they will define cable length calculations for GIS LVCC interfacing cables with the assistance of the CREO tool. Qualifications Required Bachelor's degree in Electrical Engineering from an accredited university or college At least 4 years of experience in a similar Job Family / function Skills And Abilities English (good level for daily discussion with customers and collaborators) Electrical schematic and control command of HV equipment (GIS station, AIS station, GCB, PTR) Tool skills (Need to know and know how to use tools for the job): SAP / Excel / Word Proficient in CAD software such as AutoCAD, CREO, or SolidWorks. Strong knowledge of design software like E-plan / Engineering Base (EB). Desired Characteristics Good communication Rigor Transparency Ability to work in a team and international environment Additional Information Relocation Assistance Provided: Yes

bebo Technologies is a leading complete software solution provider. bebo stands for 'be extension be offshore'. We are a business partner of QASource, inc. USA[www.QASource.com]. We offer outstanding services in the areas of software development, sustenance engineering, quality assurance and product support. bebo is dedicated to provide high-caliber offshore software services and solutions. Our goal is to 'Deliver in time-every time'. For more details visit our website: www.bebotechnologies.com Let's have a 360 tour of our bebo premises by clicking on below link: https://www.youtube.com/watch?v=S1Bgm07dPmMKey Required Skills: Bachelor's or Master’s degree in Computer Science, Data Science, or related field. 7–10 years of industry experience, with at least 5 years in machine learning roles. Advanced proficiency in Python and common ML libraries: TensorFlow, PyTorch, Scikit-learn. Experience with distributed training, model optimization (quantization, pruning), and inference at scale. Hands-on experience with cloud ML platforms: AWS (SageMaker), GCP (Vertex AI), or Azure ML. Familiarity with MLOps tooling: MLflow, TFX, Airflow, or Kubeflow; and data engineering frameworks like Spark, dbt, or Apache Beam. Strong grasp of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay). Excellent problem-solving, communication, and documentation skills.

Job Title: Senior Machine Learning Engineer (Azure ML + Databricks + MLOps) Experience: 5+ years in AI/ML Engineering Employment Type: Full-Time Job Summary: We are looking for a Senior Machine Learning Engineer with strong expertise in Azure Machine Learning and Databricks to lead the development and deployment of scalable AI/ML solutions. You’ll work with cross-functional teams to design, build, and optimize machine learning pipelines that power critical business functions. Key Responsibilities: Design, build, and deploy scalable machine learning models using Azure Machine Learning (Azure ML) and Databricks . Develop and maintain end-to-end ML pipelines for training, validation, and deployment. Collaborate with data engineers and architects to structure data pipelines on Azure Data Lake , Synapse , or Delta Lake . Integrate models into production environments using Azure ML endpoints , MLflow , or REST APIs . Monitor and maintain deployed models, ensuring performance and reliability over time. Use Databricks notebooks and PySpark to process and analyze large-scale datasets. Apply MLOps principles using tools like Azure DevOps , CI/CD pipelines , and MLflow for versioning and reproducibility. Ensure compliance with data governance, security, and responsible AI practices. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 5+ years of hands-on experience in machine learning or data science roles. Strong proficiency in Python , and experience with libraries like Scikit-learn , XGBoost , PyTorch , or TensorFlow . Deep experience with Azure Machine Learning services (e.g., workspaces, compute clusters, pipelines). Proficient in Databricks , including Spark (PySpark), notebooks, and Delta Lake. Strong understanding of MLOps, experiment tracking, model management, and deployment automation. Experience with data engineering tools (e.g., Azure Data Factory, Azure Data Lake, Azure Synapse). Preferred Skills: Azure certifications (e.g., Azure AI Engineer Associate , Azure Data Scientist Associate ). Familiarity with Kubernetes , Docker , and container-based deployments. Experience working with structured and unstructured data (NLP, time series, image data, etc.). Knowledge of cost optimization , security best practices , and scalability on Azure. Experience with A/B testing, monitoring model drift, and real-time inference. Job Types: Full-time, Permanent Benefits: Flexible schedule Paid sick time Paid time off Provident Fund Work Location: In person

About the Role: Grade Level (for internal use): 12 S&P Global Corporate About the Role : Technology Assurance Manager The Team : The Product Enablement and Assurance team is a dynamic group dedicated to driving value across S&P Global. Reporting to Tammy Wright, this team provides key services across multiple dimensions, including Technology M&A, Digital Solutions Technology Governance, FinOps, Enterprise Data Governance, DTS Risk Assurance, Vendor Management, Enterprise Architecture, and Data Driven Decisions. Our mission is to empower DTS product teams to innovate fearlessly by providing the necessary guardrails, expertise, and support. We ensure that product teams can navigate M&A, governance, risk, compliance, financial operations, and architecture effectively. Our commitment is to foster an enterprise mindset within DTS, delivering services that are secure, compliant, cost-efficient, and resilient, all while aligning with our strategic goals and standards. Responsibilities and Impact : Collaborate with technology risk management stakeholders to proactively manage risks, including tracking issues and elevated risks. Lead a technology risk and awareness committee, contributing to automation of assurance processes with alignment to the first line of defense. Govern and oversee DTS Management Action Plans (MAPs), ensuring teams track MAPs to closure and develop processes for tracking audit MAPs to risks/issues. Serve as an advisor on Digital Operational Resilience Act compliance, providing expertise to DTS. Manage Business Impact Analysis (BIA) to assess the impact of technology changes on business operations. Ensure continuous improvement in processes by tracking DTS maturity. Provide assurance that DTS covers the correct technology standards, controls, processes, and issues. Monitor and raise awareness of InfoSec exceptions within the DTS organization. Develop roadmaps in partnership with the first line of defense, focusing on risk assessments and compliance. Act as a product manager for the DTS RISK epic, ensuring alignment and prioritization across DTS teams. Drive roadmaps to improve architecture resilience and blast radius. Facilitate an annual governance review to address architectural drift. Provide assurance on key controls and processes, such as ITDR. Establish processes for managing integration and divestiture technology and cyber risks. Partner in identifying potential risks within DTS and ensure effective mitigation. Ensure DTS products comply with internal policies, standards, and regulatory requirements. Identify critical vendor relationships and address potential risks. What We’re Looking For: Basic Required Qualifications : Bachelor's degree in Information Technology, Computer Science, or a related field. Minimum of 5 years of experience in technology assurance, risk management, or a related discipline. Strong understanding of industry standards and regulatory requirements, such as Digital Operational Resilience Act (DORA). Proven experience in managing cross-functional teams and leading technology assurance initiatives. Additional Preferred Qualifications : Master’s degree in information technology, Business Administration, or a related field. Experience working with global teams and a strong global mindset. Familiarity with vendor management and governance processes. Certifications such as Certified Information Systems Auditor (CISA) or Certified Information Security Manager (CISM) are a plus. What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here . ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 317808 Posted On: 2025-07-31 Location: Gurgaon, Haryana, India

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role : Join one of the world’s largest and most innovative Media & Entertainment companies as a QA Engineer - AI/ML , where you’ll ensure the quality and reliability of cutting-edge AI and machine learning solutions that are transforming the industry. Our AI/ML-powered systems play a crucial role in optimizing content production, personalization, and consumer engagement, and your contributions will be instrumental in delivering seamless, scalable, and efficient solutions to our global audience. As a QA Engineer specializing in AI/ML, you’ll work closely with data scientists, software engineers, and product teams to rigorously test AI models, data pipelines, and machine learning platforms. Your role will involve defining and implementing robust quality assurance practices for complex AI systems, ensuring they meet the highest standards of performance, scalability, and security. If you are passionate about AI, testing, and driving quality excellence in a dynamic environment, this is your opportunity to make an impact. 1. Quality Assurance for AI/ML Models and Pipelines Develop and execute comprehensive test plans, test cases, and test scripts to validate AI/ML models and data pipelines. Perform rigorous testing of machine learning models to ensure accuracy, reliability, and robustness under various scenarios. Validate data preprocessing, feature engineering, and model training pipelines for correctness and consistency. Identify and address performance bottlenecks in AI systems, ensuring scalability for large datasets and real-time applications. Collaborate with data scientists to validate model outputs and metrics against business requirements. 2. Automation Testing and Tool Development Design and implement automated test frameworks and tools tailored for AI/ML workflows. Automate testing of model deployments, APIs, and data pipelines using industry-standard tools and frameworks. Create scripts to simulate edge cases, stress conditions, and user interactions for AI systems. Build monitoring tools to assess AI model drift, data inconsistencies, and system performance post-deployment. Continuously enhance automation coverage and testing efficiency through innovative practices. 3. Collaboration and Cross-Functional Engagement Work closely with software engineers, data engineers, and product managers to align QA strategies with project goals. Participate in code reviews, design discussions, and sprint planning to incorporate QA perspectives early in the development lifecycle. Provide actionable feedback and insights to development teams to resolve issues and improve system quality. Support end-to-end integration testing of AI/ML solutions across multiple platforms and systems. Act as a quality advocate, promoting best practices for testing and validation within the organization. 4. Governance, Compliance, and Reporting Ensure compliance with data privacy, security, and ethical AI standards during testing and deployment. Develop and maintain comprehensive documentation for QA processes, test cases, and system validations. Monitor and report on key QA metrics, including defect rates, coverage, and system reliability. Support regulatory audits and reviews by providing required testing documentation and evidence. Stay up-to-date with industry trends, tools, and practices in QA for AI/ML systems. 5. Continuous Improvement and Innovation Research and adopt emerging technologies and frameworks for AI/ML testing and validation. Drive continuous improvement initiatives to enhance the efficiency and effectiveness of QA processes. Proactively identify and resolve quality gaps in AI/ML workflows, ensuring a seamless user experience. Contribute to building a culture of quality and accountability within the AI/ML team. Mentor junior team members on QA best practices and technical skills. Qualifications & Experiences: Academic Qualifications: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field. Certifications in software testing (e.g., ISTQB, CSTE) or machine learning (e.g., AWS ML, TensorFlow Developer) are a plus. Professional Experience: 3 + years of experience in QA engineering, with at least 1 + years focused on testing AI/ML systems. Proven expertise in testing machine learning models, data pipelines, and cloud-based AI solutions. Hands-on experience with test automation tools and frameworks such as Selenium, PyTest, JUnit, or similar. Familiarity with CI/CD pipelines and tools like Jenkins, GitHub Actions, or Azure DevOps. Solid understanding of software testing methodologies, including functional, regression, performance, and stress testing. Technical Skills: Proficiency in Python or Java, with experience in writing test scripts for AI/ML applications. Knowledge of AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Experience with testing tools specific to AI/ML, such as DeepChecks or Alibi. Familiarity with data querying languages (SQL) and data processing tools (Pandas, Spark). Understanding of cloud platforms (AWS, GCP, Azure) and their AI/ML services. Other Skills: Strong analytical and problem-solving skills, with a detail-oriented approach. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team. Passion for quality and a commitment to delivering exceptional results. Ability to adapt to a fast-paced and dynamic environment while maintaining a focus on continuous improvement. Self-motivated and proactive, with a drive to stay updated on industry trends and best practices. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Additional Locations: India-Haryana, Gurgaon Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. Senior Software Engineer-MLOps We are looking for a highly skilled Senior Software Engineer – MLOps with deep expertise in building and managing production-grade ML pipelines in AWS and Azure cloud environments. This role requires a strong foundation in software engineering, DevOps principles, and ML model lifecycle automation to enable reliable and scalable machine learning operations across the organization Key Responsibilities include: Design and build robust MLOps pipelines for model training, validation, deployment, and monitoring Automate workflows using CI/CD tools such as GitLab Actions, Azure DevOps, Jenkins, or Argo Workflows Build and manage ML workloads on AWS (SageMaker Unified studio, Bedrock, EKS, Lambda, S3, Athena) and Azure (Azure ML Foundry, AKS, ADF, Blob Storage) Design secure and cost-efficient ML architecture leveraging cloud-native services Manage infrastructure using IaC tools such as Terraform, Bicep, or CloudFormation Implement cost optimization and performance tuning for cloud workloads Package ML models using Docker, and orchestrate deployments with Kubernetes on EKS/AKS Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation Integrate observability tools for model performance, drift detection, and lineage tracking (e.g., Fiddler, MLflow, Prometheus, Grafana, Azure Monitor, CloudWatch) Ensure model reproducibility, versioning, and compliance with audit and regulatory requirements Collaborate with data scientists, software engineers, DevOps, and cloud architects to operationalize AI/ML use cases Mentor junior MLOps engineers and evangelize MLOps best practices across teams Required Qualification: Bachelor's/Master’s in Computer Science, Engineering, or related discipline 10 years in Devops, with 2+ years in MLOps. Proficient with MLflow, Airflow, FastAPI, Docker, Kubernetes, and Git. Experience with feature stores (e.g., Feast), model registries, and experiment tracking. Proficiency in Devops & MLOps, Automation Cloud formation/Teraform/BICEP Requisition ID: 610750 As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most – united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do – as a global business and as a global corporate citizen. So, choosing a career with Boston Scientific (NYSE: BSX) isn’t just business, it’s personal. And if you’re a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you!

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY-Consulting – AI Enabled Automation -GenAI/Agentic – Manager We are looking to hire people with strong AI Enabled Automation skills and who are interested in applying AI in the process automation space – Azure, AI, ML, Deep Learning, NLP, GenAI , large Lang Models(LLM), RAG ,Vector DB , Graph DB, Python. At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Responsibilities: Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Technical Skills Requirements 9 to 13 years of relevant professional experience Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. Strong foundation in ML algorithms, feature engineering, and model evaluation.- Must Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP.-Must Experience in GenAI technologies — LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI.(Agentic Framework) Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Experience with multi-agent orchestration, memory, and tool integrations Experience/Implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning and reproducibility)--Good to have Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. Good understanding of data pipelines, APIs, and distributed systems. Build observability into AI systems — latency, drift, performance metrics. Strong written and verbal communication, presentation, client service and technical writing skills in English for both technical and business audiences. Strong analytical, problem solving and critical thinking skills. Ability to work under tight timelines for multiple project deliveries. What we offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. And while we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY you can be who you are and express your point of view, energy and enthusiasm, wherever you are in the world. It's how you make a difference. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

About the Role: Grade Level (for internal use): 12 S&P Global Corporate About the Role : Technology Assurance Manager The Team : The Product Enablement and Assurance team is a dynamic group dedicated to driving value across S&P Global. Reporting to Tammy Wright, this team provides key services across multiple dimensions, including Technology M&A, Digital Solutions Technology Governance, FinOps, Enterprise Data Governance, DTS Risk Assurance, Vendor Management, Enterprise Architecture, and Data Driven Decisions. Our mission is to empower DTS product teams to innovate fearlessly by providing the necessary guardrails, expertise, and support. We ensure that product teams can navigate M&A, governance, risk, compliance, financial operations, and architecture effectively. Our commitment is to foster an enterprise mindset within DTS, delivering services that are secure, compliant, cost-efficient, and resilient, all while aligning with our strategic goals and standards. Responsibilities and Impact : Collaborate with technology risk management stakeholders to proactively manage risks, including tracking issues and elevated risks. Lead a technology risk and awareness committee, contributing to automation of assurance processes with alignment to the first line of defense. Govern and oversee DTS Management Action Plans (MAPs), ensuring teams track MAPs to closure and develop processes for tracking audit MAPs to risks/issues. Serve as an advisor on Digital Operational Resilience Act compliance, providing expertise to DTS. Manage Business Impact Analysis (BIA) to assess the impact of technology changes on business operations. Ensure continuous improvement in processes by tracking DTS maturity. Provide assurance that DTS covers the correct technology standards, controls, processes, and issues. Monitor and raise awareness of InfoSec exceptions within the DTS organization. Develop roadmaps in partnership with the first line of defense, focusing on risk assessments and compliance. Act as a product manager for the DTS RISK epic, ensuring alignment and prioritization across DTS teams. Drive roadmaps to improve architecture resilience and blast radius. Facilitate an annual governance review to address architectural drift. Provide assurance on key controls and processes, such as ITDR. Establish processes for managing integration and divestiture technology and cyber risks. Partner in identifying potential risks within DTS and ensure effective mitigation. Ensure DTS products comply with internal policies, standards, and regulatory requirements. Identify critical vendor relationships and address potential risks. What We’re Looking For: Basic Required Qualifications : Bachelor's degree in Information Technology, Computer Science, or a related field. Minimum of 5 years of experience in technology assurance, risk management, or a related discipline. Strong understanding of industry standards and regulatory requirements, such as Digital Operational Resilience Act (DORA). Proven experience in managing cross-functional teams and leading technology assurance initiatives. Additional Preferred Qualifications : Master’s degree in information technology, Business Administration, or a related field. Experience working with global teams and a strong global mindset. Familiarity with vendor management and governance processes. Certifications such as Certified Information Systems Auditor (CISA) or Certified Information Security Manager (CISM) are a plus. What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here . ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 317808 Posted On: 2025-07-31 Location: Gurgaon, Haryana, India

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY-Consulting – AI Enabled Automation -GenAI/Agentic – Manager We are looking to hire people with strong AI Enabled Automation skills and who are interested in applying AI in the process automation space – Azure, AI, ML, Deep Learning, NLP, GenAI , large Lang Models(LLM), RAG ,Vector DB , Graph DB, Python. At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Responsibilities: Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Technical Skills Requirements 9 to 13 years of relevant professional experience Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. Strong foundation in ML algorithms, feature engineering, and model evaluation.- Must Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP.-Must Experience in GenAI technologies — LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI.(Agentic Framework) Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Experience with multi-agent orchestration, memory, and tool integrations Experience/Implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning and reproducibility)--Good to have Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. Good understanding of data pipelines, APIs, and distributed systems. Build observability into AI systems — latency, drift, performance metrics. Strong written and verbal communication, presentation, client service and technical writing skills in English for both technical and business audiences. Strong analytical, problem solving and critical thinking skills. Ability to work under tight timelines for multiple project deliveries. What we offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. And while we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY you can be who you are and express your point of view, energy and enthusiasm, wherever you are in the world. It's how you make a difference. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY-Consulting – AI Enabled Automation -GenAI/Agentic – Manager We are looking to hire people with strong AI Enabled Automation skills and who are interested in applying AI in the process automation space – Azure, AI, ML, Deep Learning, NLP, GenAI , large Lang Models(LLM), RAG ,Vector DB , Graph DB, Python. At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Responsibilities: Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Technical Skills Requirements 9 to 13 years of relevant professional experience Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. Strong foundation in ML algorithms, feature engineering, and model evaluation.- Must Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP.-Must Experience in GenAI technologies — LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI.(Agentic Framework) Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Experience with multi-agent orchestration, memory, and tool integrations Experience/Implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning and reproducibility)--Good to have Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. Good understanding of data pipelines, APIs, and distributed systems. Build observability into AI systems — latency, drift, performance metrics. Strong written and verbal communication, presentation, client service and technical writing skills in English for both technical and business audiences. Strong analytical, problem solving and critical thinking skills. Ability to work under tight timelines for multiple project deliveries. What we offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. And while we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY you can be who you are and express your point of view, energy and enthusiasm, wherever you are in the world. It's how you make a difference. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role Join one of the world’s largest and most innovative Media & Entertainment companies as a QA Engineer - AI/ML , where you’ll ensure the quality and reliability of cutting-edge AI and machine learning solutions that are transforming the industry. Our AI/ML-powered systems play a crucial role in optimizing content production, personalization, and consumer engagement, and your contributions will be instrumental in delivering seamless, scalable, and efficient solutions to our global audience. As a QA Engineer specializing in AI/ML, you’ll work closely with data scientists, software engineers, and product teams to rigorously test AI models, data pipelines, and machine learning platforms. Your role will involve defining and implementing robust quality assurance practices for complex AI systems, ensuring they meet the highest standards of performance, scalability, and security. If you are passionate about AI, testing, and driving quality excellence in a dynamic environment, this is your opportunity to make an impact. Quality Assurance for AI/ML Models and Pipelines Develop and execute comprehensive test plans, test cases, and test scripts to validate AI/ML models and data pipelines. Perform rigorous testing of machine learning models to ensure accuracy, reliability, and robustness under various scenarios. Validate data preprocessing, feature engineering, and model training pipelines for correctness and consistency. Identify and address performance bottlenecks in AI systems, ensuring scalability for large datasets and real-time applications. Collaborate with data scientists to validate model outputs and metrics against business requirements. Automation Testing and Tool Development Design and implement automated test frameworks and tools tailored for AI/ML workflows. Automate testing of model deployments, APIs, and data pipelines using industry-standard tools and frameworks. Create scripts to simulate edge cases, stress conditions, and user interactions for AI systems. Build monitoring tools to assess AI model drift, data inconsistencies, and system performance post-deployment. Continuously enhance automation coverage and testing efficiency through innovative practices. Collaboration and Cross-Functional Engagement Work closely with software engineers, data engineers, and product managers to align QA strategies with project goals. Participate in code reviews, design discussions, and sprint planning to incorporate QA perspectives early in the development lifecycle. Provide actionable feedback and insights to development teams to resolve issues and improve system quality. Support end-to-end integration testing of AI/ML solutions across multiple platforms and systems. Act as a quality advocate, promoting best practices for testing and validation within the organization. Governance, Compliance, and Reporting Ensure compliance with data privacy, security, and ethical AI standards during testing and deployment. Develop and maintain comprehensive documentation for QA processes, test cases, and system validations. Monitor and report on key QA metrics, including defect rates, coverage, and system reliability. Support regulatory audits and reviews by providing required testing documentation and evidence. Stay up-to-date with industry trends, tools, and practices in QA for AI/ML systems. Continuous Improvement and Innovation Research and adopt emerging technologies and frameworks for AI/ML testing and validation. Drive continuous improvement initiatives to enhance the efficiency and effectiveness of QA processes. Proactively identify and resolve quality gaps in AI/ML workflows, ensuring a seamless user experience. Contribute to building a culture of quality and accountability within the AI/ML team. Mentor junior team members on QA best practices and technical skills. Qualifications & Experiences Academic Qualifications: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field. Certifications in software testing (e.g., ISTQB, CSTE) or machine learning (e.g., AWS ML, TensorFlow Developer) are a plus. Professional Experience 3+ years of experience in QA engineering, with at least 1+ years focused on testing AI/ML systems. Proven expertise in testing machine learning models, data pipelines, and cloud-based AI solutions. Hands-on experience with test automation tools and frameworks such as Selenium, PyTest, JUnit, or similar. Familiarity with CI/CD pipelines and tools like Jenkins, GitHub Actions, or Azure DevOps. Solid understanding of software testing methodologies, including functional, regression, performance, and stress testing. Technical Skills Proficiency in Python or Java, with experience in writing test scripts for AI/ML applications. Knowledge of AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Experience with testing tools specific to AI/ML, such as DeepChecks or Alibi. Familiarity with data querying languages (SQL) and data processing tools (Pandas, Spark). Understanding of cloud platforms (AWS, GCP, Azure) and their AI/ML services. Other Skills Strong analytical and problem-solving skills, with a detail-oriented approach. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team. Passion for quality and a commitment to delivering exceptional results. Ability to adapt to a fast-paced and dynamic environment while maintaining a focus on continuous improvement. Self-motivated and proactive, with a drive to stay updated on industry trends and best practices. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Position: Head – Digital Sales Group (DSG), Domestic Business, Airtel Business Location: Noida Function: Marketing Experience: 8+ years Reports to: Head, Marketing About the role: As the Head of Digital Sales Group (DSG) for Domestic Business at Airtel Business, you will spearhead our digital-first enterprise sales engine. This is a critical leadership role focused on building and scaling a high-velocity digital sales function that drives pipeline, accelerates conversion, and supports our ambitious growth in the SME and Enterprise segment. You will lead a team of digital sales representatives, marketing automation specialists, and inside sales professionals to: Managing a large team of digital sales representatives and drive actions to improve their productivity across different segments Work closely with Airtel Business segment leaders to put together a clear marketing plan into action Drive pipeline growth through targeted digital outreach across multiple channels including LinkedIn, Salesforce, email, enrichment tools, and webinars. Manage end-to-end funnel from lead qualification to conversion in collaboration with GTM, product, and field sales teams. Strengthen sales productivity by building digital playbooks, processes, and training modules. Leverage data and CRM insights to continuously improve contact strategies, conversion rates, and revenue per rep. Innovate the digital sales tech stack by evaluating and implementing modern tools (Salesforce, Lusha, Apollo, Drift, Outreach, etc.). Partner closely with Product Marketing teams to ensure DSG efforts are aligned with Airtel Businesses’ broader marketing priorities. This role is at the intersection of sales, marketing, and technology – ideal for a commercially-minded leader who thrives in a fast-paced, digitally enabled, B2B enterprise environment. Ideal candidate profile: We’re looking for a high-energy, results-driven digital sales leader with a strong understanding of enterprise B2B dynamics. The ideal candidate will bring: Must-Have Qualifications: 10–14 years of experience in B2B inside sales, digital sales, or revenue operations, preferably in telecom, SaaS, enterprise tech , or managed services. Proven success leading a digital sales or SDR function with measurable pipeline and revenue impact. Deep experience working with Salesforce CRM , lead gen platforms (e.g., Apollo, Lusha, LinkedIn Sales Navigator) , and sales automation workflows . Ability to manage and scale inside sales teams , including hiring, training, and performance optimization. Strong analytical skills and familiarity with sales KPIs , conversion tracking, lead scoring, and dashboarding. Preferred Skills: Experience in a high-growth B2B business targeting SMEs and enterprises . Understanding of the telecom and technology landscape Strong collaboration skills to work cross-functionally with product, field sales, and brand marketing. Excellent communication and stakeholder management skills – ability to influence across levels. Why Join Us? At Airtel Business, you’ll be part of a fast-transforming organization at the forefront of India’s enterprise digital revolution. You’ll have the opportunity to shape a scalable, high-impact digital sales model in one of India’s most trusted and dynamic brands.

At Airtel , we’re not just scaling connectivity—we’re redefining how India experiences digital services. With 400M+ customers across telecom, financial services, and entertainment, our impact is massive. But behind every experience is an opportunity to make it smarter . We're looking for a Product Manager – AI to drive next-gen intelligence for our customers and business. AI is a transformational technology and we are looking or skilled product managers who will work on leveraging AI to power everything from our digital platforms to customer experience. You’ll work at the intersection of machine learning, product design, and systems thinking to deliver AI-driven products that create tangible business impact—fast. What You’ll Do Lead and contribute to AI-Powered Product Strategy Define product vision and strategy for AI-led initiatives that enhance productivity, automate decisions, and personalise user interactions across Airtel platforms. Translate Business Problems into AI Opportunities Partner with operations, engineering, and data science to surface high-leverage AI use cases across workforce management, customer experience, and process automation. Build & Scale ML-Driven Products Define data product requirements, work closely with ML engineers to develop models, and integrate intelligent workflows that continuously learn and adapt. Own Product Execution End-to-End Drive roadmaps, lead cross-functional teams, launch MVPs, iterate based on real-world feedback, and scale solutions with measurable ROI. What You Need to be Successful Influential Communication - Craft clarity from complexity. You can tailor messages for execs, engineers, and field teams alike—translating AI into business value. Strategic Prioritisation - Balance business urgency with technical feasibility. You can decide what not to build, and defend those decisions with data and a narrative Systems Thinking - You can sees the big picture —how decisions in one area ripple across the business, tech stack, and user experience. High Ownership & Accountability - Operate with a founder mindset. You don't wait for direction — you can rally teams, removes blockers, deal with tough stakeholders and drives outcomes. Adaptability - You thrive in ambiguity and pivot quickly without losing sight of long-term vision—key in fast-moving digital organizations. Skills You'll Need AI / ML Fundamentals Understanding of ML model types: Supervised, unsupervised, reinforcement learning Common algorithms: Linear/logistic regression, decision trees, clustering, neural networks Model lifecycle: Training, validation, testing, tuning, deployment, monitoring Understanding of LLMs, transformers, diffusion models, vector search, etc. Familiarity with GenAI product architecture: Retrieval-Augmented Generation (RAG), prompt tuning, fine-tuning Awareness of real-time personalization, recommendation systems, ranking algorithms, etc Data Fluency Understanding Data pipelines Working knowledge of SQL and Python for analysis Understanding of data annotation, labeling, and versioning Ability to define data requirements and assess data readiness AI Product Development Defining ML problem scope: Classification vs. regression vs. ranking vs. generation Model evaluation metrics: Precision, recall, etc. A/B testing & online experimentation for ML-driven experiences ML Infrastructure Awareness Know what it takes to make things work and happen. Model deployment techniques: Batch vs real-time inference, APIs, model serving Monitoring & drift detection: How to ensure models continue performing over time Familiarity with ML platforms/tools: TensorFlow, PyTorch, Hugging Face, Vertex AI, SageMaker, etc. (at a product level) Understanding latency, cost, and resource implications of ML choices AI Ethics & Safety We care deeply about our customers, their privacy and compliance to regulation. Understand Bias and fairness in models: How to detect and mitigate them Explainability & transparency: Importance for user trust and regulation Privacy & security: Understanding implications of sensitive or PII data in AI Alignment and guardrails in generative AI systems Preferred Qualifications Experienced Machine Learning/Artificial Intelligence PMs Experience building 0-1 products, scaled platforms/ecosystem products, or ecommerce Bachelor's degree in Computer Science, Engineering, Information Systems, Analytics, Mathematics Masters degree in Business Why Airtel Digital? Massive Scale : Your products will impact 400M+ users across sectors Real-World Relevance : Solve meaningful problems for our customers — protecting our customers, spam & fraud prevention, personalised experiences, connecting homes. Agility Meets Ambition : Work like a startup with the resources of a telecom giant AI That Ships : We don’t just run experiments. We deploy models and measure real-world outcomes Leadership Access : Collaborate closely with CXOs and gain mentorship from India’s top product and tech leaders

About the Role: Grade Level (for internal use): 12 S&P Global Corporate About the Role : Technology Assurance Manager The Team : The Product Enablement and Assurance team is a dynamic group dedicated to driving value across S&P Global. Reporting to Tammy Wright, this team provides key services across multiple dimensions, including Technology M&A, Digital Solutions Technology Governance, FinOps, Enterprise Data Governance, DTS Risk Assurance, Vendor Management, Enterprise Architecture, and Data Driven Decisions. Our mission is to empower DTS product teams to innovate fearlessly by providing the necessary guardrails, expertise, and support. We ensure that product teams can navigate M&A, governance, risk, compliance, financial operations, and architecture effectively. Our commitment is to foster an enterprise mindset within DTS, delivering services that are secure, compliant, cost-efficient, and resilient, all while aligning with our strategic goals and standards. Responsibilities and Impact : Collaborate with technology risk management stakeholders to proactively manage risks, including tracking issues and elevated risks. Lead a technology risk and awareness committee, contributing to automation of assurance processes with alignment to the first line of defense. Govern and oversee DTS Management Action Plans (MAPs), ensuring teams track MAPs to closure and develop processes for tracking audit MAPs to risks/issues. Serve as an advisor on Digital Operational Resilience Act compliance, providing expertise to DTS. Manage Business Impact Analysis (BIA) to assess the impact of technology changes on business operations. Ensure continuous improvement in processes by tracking DTS maturity. Provide assurance that DTS covers the correct technology standards, controls, processes, and issues. Monitor and raise awareness of InfoSec exceptions within the DTS organization. Develop roadmaps in partnership with the first line of defense, focusing on risk assessments and compliance. Act as a product manager for the DTS RISK epic, ensuring alignment and prioritization across DTS teams. Drive roadmaps to improve architecture resilience and blast radius. Facilitate an annual governance review to address architectural drift. Provide assurance on key controls and processes, such as ITDR. Establish processes for managing integration and divestiture technology and cyber risks. Partner in identifying potential risks within DTS and ensure effective mitigation. Ensure DTS products comply with internal policies, standards, and regulatory requirements. Identify critical vendor relationships and address potential risks. What We’re Looking For: Basic Required Qualifications : Bachelor's degree in Information Technology, Computer Science, or a related field. Minimum of 5 years of experience in technology assurance, risk management, or a related discipline. Strong understanding of industry standards and regulatory requirements, such as Digital Operational Resilience Act (DORA). Proven experience in managing cross-functional teams and leading technology assurance initiatives. Additional Preferred Qualifications : Master’s degree in information technology, Business Administration, or a related field. Experience working with global teams and a strong global mindset. Familiarity with vendor management and governance processes. Certifications such as Certified Information Systems Auditor (CISA) or Certified Information Security Manager (CISM) are a plus. What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here . ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 317808 Posted On: 2025-07-31 Location: Gurgaon, Haryana, India

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for contributing to the development and deployment of machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms as a part of a larger team. Contributes to translating application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Contributes to developing ways to use machine learning to solve problems and discover new products, working on a portion of the problem and collaborating with more senior researchers as needed. Works with moderate guidance in own area of knowledge. Job Description Core Responsibilities About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers, and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to support dynamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and exploration of emerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 3+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts Certifications in cloud architecture, ML engineering, or data science specialization Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 2-5 Years

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for developing and deploying machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms. Translates application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to use machine learning to solve problems and discover new products. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience. Job Description About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to supportnamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and explorationemerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 5+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts. Certifications in cloud architecture, ML engineering, or data science specializations, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports. Contributes to the company by creating patents, Application Programming Interfaces (APIs). Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 5-7 Years

About AiSensy AiSensy is a WhatsApp based Marketing & Engagement platform helping businesses like Adani, Delhi Transport Corporation, Yakult, Godrej, Aditya Birla Hindalco, Wipro, Asian Paints, India Today Group, Skullcandy, Vivo, Physicswallah, and Cosco grow their revenues via WhatsApp. Enabling 100,000+ Businesses with WhatsApp Engagement & Marketing 400 Crores+ WhatsApp Messages exchanged between Businesses and Users via AiSensy per year Working with top brands like Delhi Transport Corporation, Vivo, Physicswallah & more High Impact as Businesses drive 25-80% Revenues using AiSensy Platform Mission-Driven and Growth Stage Startup backed by Marsshot.vc, Bluelotus.vc & 50+ Angel Investors Role Overview We are looking for a Senior Machine Learning Engineer to lead the development and deployment of cutting-edge AI/ML systems with a strong focus on LLMs, Retrieval-Augmented Generation (RAG), AI agents , and intelligent automation. You will work closely with cross-functional teams to translate business needs into AI solutions, bringing your expertise in building scalable ML infrastructure, deploying models in production, and staying at the forefront of AI innovation. Key Responsibilities AI & ML System Development Design, develop, and optimize end-to-end ML models using LLMs, transformer architectures, and custom RAG frameworks. Fine-tune and evaluate generative and NLP models for business-specific applications such as conversational flows, auto-replies, and intelligent routing. Lead prompt engineering and build autonomous AI agents capable of executing multi-step reasoning. Infrastructure, Deployment & MLOps Architect and automate scalable training, validation, and deployment pipelines using tools like MLflow, SageMaker, or Vertex AI. Integrate ML models with APIs, databases (vector/graph), and production services ensuring performance, reliability, and traceability. Monitor model performance in real-time, and implement A/B testing, drift detection, and re-training pipelines. Data & Feature Engineering Work with structured, unstructured, and semi-structured data (text, embeddings, chat history). Build and manage vector databases (e.g., Pinecone, Weaviate) and graph-based retrieval systems. Ensure high-quality data ingestion, feature pipelines, and scalable pre-processing workflows. Team Collaboration & Technical Leadership Collaborate with product managers, software engineers, and stakeholders to align AI roadmaps with product goals. Mentor junior engineers and establish best practices in experimentation, reproducibility, and deployment. Stay updated on the latest in AI/ML (LLMs, diffusion models, multi-modal learning), and drive innovation in applied use cases. Required Qualifications Bachelor’s/Master’s degree in Computer Science, Engineering, AI/ML, or a related field from a Tier 1 institution (IIT, NIT, IIIT or equivalent). 2+ years of experience building and deploying machine learning models in production. Expertise in Python and known the frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn . Hands-on experience with transformer models , LLMs , LangChain , LangGraph, OpenAI API , or similar. Deep knowledge of machine learning algorithms , model evaluation, hyperparameter tuning, and optimization. Experience working with cloud platforms (AWS, GCP, or Azure) and ML Ops tools (MLflow, Airflow, Kubernetes). Strong understanding of SQL , data engineering concepts, and working with large-scale datasets. Preferred Qualifications Experience with prompt tuning, agentic AI systems , or multi-modal learning . Familiarity with vector search systems (e.g., Pinecone, FAISS, Milvus) and knowledge graphs . Contributions to open-source AI/ML projects or publications in AI journals/conferences. Experience in building conversational AI or smart assistants using WhatsApp or similar messaging APIs. Why Join AiSensy? Build AI that directly powers growth for 100,000+ businesses. Work on cutting-edge technologies like LLMs, RAG, and AI agents in real production environments. High ownership, fast iterations, and impact-focused work. Ready to build intelligent systems that redefine communication? Apply now and join the AI revolution at AiSensy .

We’re Hiring: Machine Learning Engineer (Part-Time | Flexible Remote) Are you an experienced ML Engineer looking for a flexible, part-time opportunity to work on real-world impact projects? Join us in building intelligent systems that match candidates to projects using structured skills, assessments, and feedback data. This is your chance to own end-to-end ML pipelines and work on meaningful automation in the HRTech space — all on your own schedule. 🔍 Role Overview: We’re looking for an ML Engineer to architect and deploy predictive models that power candidate–project matching intelligence , leveraging structured applicant data. You'll design scalable ML workflows and inference pipelines on AWS . 🔧 Key Responsibilities: Build data pipelines to ingest & preprocess applicant data (skills, assessments, feedback) Engineer task-specific features and transformation logic Train predictive models (logistic regression, XGBoost, etc.) on SageMaker Automate batch ETL, retraining flows, and storage with AWS S3 Deploy inference endpoints with Lambda , and integrate with systems in production Monitor model drift, performance, and feedback loops for continuous learning Document architecture, workflows, and ensure explainability ✅ You’ll Need: 4–6+ years in ML/AI engineering roles Strong command of Python, scikit-learn, XGBoost , and feature engineering Proven experience with AWS ML stack : SageMaker, Lambda, S3 Hands-on SQL/NoSQL and automated data workflows Familiarity with CI/CD for ML (CodePipeline, CodeBuild, etc.) Ability to independently own schema, features, and model delivery Bachelor’s or Master’s in CS, Engineering, or related field ⭐ Bonus Points For: NLP experience (extracting features from feedback/comments) Familiarity with serverless architectures Background in recruitment, talent platforms, or skills-matching system 👉 Apply now or DM us to know more. #Hiring #MachineLearning #MLJobs #RemoteJobs #PartTime #AWS #HRTech #MLOps #AI #RecruitmentTech #SageMaker #FlexibleWork