713 Mlflow Jobs - Page 4

Role Overview As a Test Automation Lead at Dailoqa, you’ll architect and implement robust testing frameworks for both software and AI/ML systems. You’ll bridge the gap between traditional QA and AI-specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance. Key Responsibilities Test Automation Strategy & Framework Design Design and implement scalable test automation frameworks for frontend (UI/UX) , backend APIs , and AI/ML model-serving endpoints using tools like Selenium, Playwright, Postman, or custom Python/Java solutions. Build GenAI-specific test suites for validating prompt outputs, LLM-based chat interfaces, RAG systems, and vector search accuracy. Develop performance testing strategies for AI pipelines (e.g., model inference latency, resource utilization). Continuous Testing & CI/CD Integration Establish and maintain continuous testing pipelines integrated with GitHub Actions, Jenkins, or GitLab CI/CD. Implement shift-left testing by embedding automated checks into development workflows (e.g., unit tests, contract testing). AI/ML Model Validation Collaborate with data scientists to test AI/ML models for accuracy , fairness , stability , and bias mitigation using tools like TensorFlow Model Analysis or MLflow. Validate model drift and retraining pipelines to ensure consistent performance in production. Quality Metrics & Reporting Define and track KPIs. Test coverage (code, data, scenarios) Defect leakage rate Automation ROI (time saved vs. maintenance effort) Model accuracy thresholds Report risks and quality trends to stakeholders in sprint reviews. Drive adoption of AI-specific testing tools (e.g., LangChain for LLM testing, Great Expectations for data validation). Soft Skills Strong problem-solving skills for balancing speed and quality in fast-paced AI development. Ability to communicate technical risks to non-technical stakeholders. Collaborative mindset to work with cross-functional teams (data scientists, ML engineers, DevOps). Requirements Technical Requirements Must-Have 5–8 years in test automation, with 2+ years validating AI/ML systems. Expertise in: Automation tools: Selenium, Playwright, Cypress, REST Assured, Locust/JMeter CI/CD: Jenkins, GitHub Actions, GitLab AI/ML testing: Model validation, drift detection, GenAI output evaluation Languages: Python, Java, or JavaScript Certifications: ISTQB Advanced, CAST, or equivalent. Experience with MLOps tools: MLflow, Kubeflow, TFX Familiarity with vector databases (Pinecone, Milvus) and RAG workflows. Strong programming/scripting experience in JavaScript, Python, Java, or similar Experience with API testing, UI testing, and automated pipelines Understanding of AI/ML model testing, output evaluation, and non-deterministic behavior validation Experience with testing AI chatbots, LLM responses, prompt engineering outcomes, or AI fairness/bias Familiarity with MLOps pipelines and automated validation of model performance in production Exposure to Agile/Scrum methodology and tools like Azure Boards Show more Show less

About the Open Position Join us as Cloud Engineer at Dailoqa , where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems. To be successful as Cloud Engineer you should have experience with: Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management Deep expertise in one or more cloud platforms: AWS, Azure, GCP Strong experience in containerization and orchestration (Docker, Kubernetes, Helm) Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc. Proficiency in scripting languages (Python, Bash, PowerShell) Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML Strong understanding of DevOps principles applied to ML workflows. Key Responsibilities may include: · Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms. · Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation. · Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows. · Ensure version control, repeatability, and compliance across all infrastructure components. · Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor. · Optimize performance and resource utilization of AI workloads including GPU-based training/inference Experience with Snowflake, Databricks for collaborative ML development and scalable data processing. Understanding model interpretability, responsible AI, and governance. Contributions to open-source MLOps tools or communities. Strong leadership, communication, and cross-functional collaboration skills. Knowledge of data privacy, model governance, and regulatory compliance in AI systems. Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines. Show more Show less

About Us: Waltcorp is at the forefront of cloud engineering, helping businesses transform their operations by leveraging the power of Google Cloud Platform (GCP) . We are seeking a skilled and visionary GCP DevOps Solutions Architect – ML/AI Focus to design and implement cloud solutions that address our clients' complex business challenges. Key Responsibilities: Solution Design: Collaborate with stakeholders to understand business requirements and design scalable, secure, and high-performing GCP cloud architectures . Technical Leadership: Serve as a technical advisor, guiding teams on GCP best practices, services, and tools to optimize performance, security, and cost efficiency. Infrastructure Development: Architect and oversee the deployment of cloud solutions using GCP services such as Compute Engine, Cloud Storage, Cloud Functions, Cloud SQL , and more. Infrastructure as Code (IaC) & Cloud Automation: Design, implement, and manage infrastructure using Terraform, Google Cloud Deployment Manager , or Pulumi . Automate provisioning of compute, storage, and networking resources using GCP services like Compute Engine, Cloud Storage, VPC, IAM, GKE (Google Kubernetes Engine), Cloud Run . Implement and maintain CI/CD pipelines (using Cloud Build, Jenkins, GitHub Actions , or GitLab CI ). ML Model Deployment & Automation (MLOps): Build and optimize end-to-end ML pipelines using Vertex AI Pipelines, Kubeflow , or MLflow . Automate training, testing, validation, and deployment of ML models in staging and production environments. Support model versioning, reproducibility, and lineage tracking using tools like DVC, Vertex AI Model Registry , or MLflow . Monitoring & Logging: Implement monitoring for both infrastructure and ML workflows using Cloud Monitoring, Prometheus, Grafana, Vertex AI Model Monitoring . Set up alerting for anomalies in ML model performance (data drift, concept drift). Ensure application logs, model outputs, and system metrics are centralized and accessible. Containerization & Orchestration: Containerize ML workloads using Docker and orchestrate using GKE or Cloud Run . Optimize resource usage through autoscaling and right-sizing of ML workloads in containers. Data & Experiment Management: Integrate with data versioning tools (e.g., DVC or LakeFS ) to track datasets used in model training. Enable experiment tracking using MLflow, Weights & Biases , or Vertex AI Experiments . Support reproducible research and automated experimentation pipelines. Client Engagement: Communicate complex technical solutions to non-technical stakeholders and deliver high-level architectural designs, presentations, and proposals. Integration and Migration: Plan and execute cloud migration strategies, integrating existing on-premises systems with GCP infrastructure . Security and Compliance: Implement robust security measures, including IAM policies, encryption, and monitoring , to ensure compliance with industry standards and regulations. Documentation: Develop and maintain detailed technical documentation for architecture designs, deployment processes, and configurations. Continuous Improvement: Stay current with GCP advancements and emerging trends , recommending updates to architecture strategies and tools. Qualifications: Educational Background: Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience). Experience: 3+ years of experience in cloud architecture, with a focus on GCP . Technical Expertise: Strong knowledge of GCP core services , including compute, storage, networking, and database solutions. Proficiency in Infrastructure as Code (IaC) tools like Terraform , Deployment Manager , or Pulumi . Experience with containerization and orchestration tools (e.g., Docker , Kubernetes , GKE , or Cloud Run ). Understanding of DevOps practices, CI/CD pipelines, and automation . Strong command of networking concepts such as VPCs, load balancing , and firewall rules . Familiarity with scripting languages like Python or Bash . Preferred Qualifications: Google Cloud Certified – Professional Cloud Architect or Professional DevOps Engineer . Expertise in engineering and maintaining MLOps and AI applications . Experience in hybrid cloud or multi-cloud environments . Familiarity with monitoring and logging tools such as Cloud Monitoring, ELK Stack , or Datadog . [CLOUD-GCDEPS-J25] Show more Show less

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Are you excited by the challenge of pushing the boundaries with the latest advancements in computer vision and multi-modal Large Language Models? Does the idea of working on the edge of AI research and applying it to create industry-defining software solutions resonate with you? At Nielsen Sports, we provide the most comprehensive and trusted data and analytics for the global sports ecosystem, helping clients understand media value, fan behavior, and sponsorship effectiveness. This role will place you at the forefront of this mission, architecting and implementing sophisticated AI systems that unlock novel insights from complex multimedia sports data. We are looking for Principal / Sr Principal Engineers to join us on this mission. Key Responsibilities: Technical Leadership & Architecture: Lead the design and architecture of scalable and robust AI/ML systems, particularly focusing on computer vision and LLM applications for sports media analysis Model Development & Training: Spearhead the development, training, and fine-tuning of sophisticated deep learning models (e.g., object detectors like RT-DETR, custom classifiers, generative models) on large-scale, domain-specific datasets (like sports imagery and video) Generalized Object Detection: Develop and implement advanced computer vision models capable of identifying a wide array of visual elements (e.g., logos, brand assets, on-screen graphics) in diverse and challenging sports content, including those not seen during training LLM & GenAI Integration: Explore and implement solutions leveraging LLMs and Generative AI for tasks such as content summarization, insight generation, data augmentation, and model validation (e.g., using vision models to verify detections) System Implementation & Deployment: Build and deploy production-ready AI/ML pipelines, ensuring efficiency, scalability, and maintainability. This includes developing APIs and integrating models into broader Nielsen Sports platforms UI/UX for AI Tools: Guide or contribute to the development of internal tools and simple user interfaces (using frameworks like Streamlit, Gradio, or web stacks) to showcase model capabilities, facilitate data annotation, and allow for human-in-the-loop validation Research & Innovation: Stay at the forefront of advancements in computer vision, LLMs, and related AI fields. Evaluate and prototype new technologies and methodologies to drive innovation within Nielsen Sports Mentorship & Collaboration: Mentor junior engineers, share knowledge, and collaborate effectively with cross-functional teams including product managers, data scientists, and operations Performance Optimization: Optimize model performance for speed and accuracy, and ensure efficient use of computational resources (including cloud platforms like AWS, GCP, or Azure) Data Strategy: Contribute to data acquisition, preprocessing, and augmentation strategies to enhance model performance and generalization Required Qualifications: Bachelors of Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field 5+ years (for Principal / MTS-4) / 8+ years (for Senior Principal / MTS-5) of hands-on experience in developing and deploying AI/ML models, with a strong focus on Computer Vision Proven experience in training deep learning models for object detection (e.g., YOLO, Faster R-CNN, DETR variants like RT-DETR) on custom datasets Experience in finetuning LLMs like Llama 2/3, Mistral, or open-source models available on Hugging Face using libraries such as Hugging Face Transformers, PEFT, or specialized frameworks like Axolotl/Unsloth Proficiency in Python and deep learning frameworks such as PyTorch (preferred) or TensorFlow/Keras Demonstrable experience with Multi Modal Large Language Models (LLMs) and their application, including familiarity with transformer architectures and fine-tuning techniques Experience with developing simple UIs for model interaction or data annotation (e.g., using Streamlit, Gradio, Flask/Django) Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and lifecycle management (e.g., Docker, Kubernetes, Kubeflow, MLflow) Strong software engineering fundamentals, including code versioning (Git), testing, and CI/CD practices Excellent problem-solving skills and the ability to work with complex, large-scale datasets Strong communication and collaboration skills, with the ability to convey complex technical concepts to diverse audiences Full Stack Development experience in any one stack Preferred Qualifications / Bonus Skills: Experience with Generative AI vision models for tasks like image analysis, description, or validation Track record of publications in top-tier AI/ML/CV conferences or journals Experience working with sports data (broadcast feeds, social media imagery, sponsorship analytics) Proficiency in cloud computing platforms (AWS, GCP, Azure) and their AI/ML services Experience with video processing and analysis techniques Familiarity with data pipeline and distributed computing tools (e.g., Apache Spark, Kafka) Demonstrated ability to lead technical projects and mentor team members Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @ nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law. Show more Show less

It's about Being What's next. What's in it for you? A Data Scientist for AI Products (Global) will be responsible for working in the Artificial Intelligence team, Linde's AI global corporate division engaged with real business challenges and opportunities in multiple countries. Focus of this role is to support the AI team with extending existing and building new AI products for a vast amount of uses cases across Linde’s business and value chain. You'll collaborate across different business and corporate functions in international team composed of Project Managers, Data Scientists, Data and Software Engineers in the AI team and others in the Linde's Global AI team. As a Data Scientist AI, you will support Linde’s AI team with extending existing and building new AI products for a vast amount of uses cases across Linde’s business and value chain" At Linde, the sky is not the limit. If you’re looking to build a career where your work reaches beyond your job description and betters the people with whom you work, the communities we serve, and the world in which we all live, at Linde, your opportunities are limitless. Be Linde. Be Limitless. Team Making an impact. What will you do? You will work directly with a variety of different data sources, types and structures to derive actionable insights Develop, customize and manage AI software products based on Machine and Deep Learning backends will be your tasks Your role includes strong support on replication of existing products and pipelines to other systems and geographies In addition to that you will support in architectural design and defining data requirements for new developments It will be your responsibility to interact with business functions in identifying opportunities with potential business impact and to support development and deployment of models into production Winning in your role. Do you have what it takes? You have a Bachelor or master’s degree in data science, Computational Statistics/Mathematics, Computer Science, Operations Research or related field You have a strong understanding of and practical experience with Multivariate Statistics, Machine Learning and Probability concepts Further, you gained experience in articulating business questions and using quantitative techniques to arrive at a solution using available data You demonstrate hands-on experience with preprocessing, feature engineering, feature selection and data cleansing on real world datasets Preferably you have work experience in an engineering or technology role You bring a strong background of Python and handling large data sets using SQL in a business environment (pandas, numpy, matplotlib, seaborn, sklearn, keras, tensorflow, pytorch, statsmodels etc.) to the role In addition you have a sound knowledge of data architectures and concepts and practical experience in the visualization of large datasets, e.g. with Tableau or PowerBI Result driven mindset and excellent communication skills with high social competence gives you the ability to structure a project from idea to experimentation to prototype to implementation Very good English language skills are required As a plus you have hands-on experience with DevOps and MS Azure, experience in Azure ML, Kedro or Airflow, experience in MLflow or similar Why you will love working for us! Linde is a leading global industrial gases and engineering company, operating in more than 100 countries worldwide. We live our mission of making our world more productive every day by providing high-quality solutions, technologies and services which are making our customers more successful and helping to sustain and protect our planet. On the 1st of April 2020, Linde India Limited and Praxair India Private Limited successfully formed a joint venture, LSAS Services Private Limited. This company will provide Operations and Management (O&M) services to both existing organizations, which will continue to operate separately. LSAS carries forward the commitment towards sustainable development, championed by both legacy organizations. It also takes ahead the tradition of the development of processes and technologies that have revolutionized the industrial gases industry, serving a variety of end markets including chemicals & refining, food & beverage, electronics, healthcare, manufacturing, and primary metals. Whatever you seek to accomplish, and wherever you want those accomplishments to take you, a career at Linde provides limitless ways to achieve your potential, while making a positive impact in the world. Be Linde. Be Limitless. Have we inspired you? Let's talk about it! We are looking forward to receiving your complete application (motivation letter, CV, certificates) via our online job market. Any designations used of course apply to persons of all genders. The form of speech used here is for simplicity only. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, pregnancy, sexual orientation, gender identity or expression, or any other reason prohibited by applicable law. Praxair India Private Limited acts responsibly towards its shareholders, business partners, employees, society and the environment in every one of its business areas, regions and locations across the globe. The company is committed to technologies and products that unite the goals of customer value and sustainable development. Show more Show less

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Are you excited by the challenge of pushing the boundaries with the latest advancements in computer vision and multi-modal Large Language Models? Does the idea of working on the edge of AI research and applying it to create industry-defining software solutions resonate with you? At Nielsen Sports, we provide the most comprehensive and trusted data and analytics for the global sports ecosystem, helping clients understand media value, fan behavior, and sponsorship effectiveness. This role will place you at the forefront of this mission, architecting and implementing sophisticated AI systems that unlock novel insights from complex multimedia sports data. We are looking for Principal / Sr Principal Engineers to join us on this mission. Key Responsibilities: Technical Leadership & Architecture: Lead the design and architecture of scalable and robust AI/ML systems, particularly focusing on computer vision and LLM applications for sports media analysis Model Development & Training: Spearhead the development, training, and fine-tuning of sophisticated deep learning models (e.g., object detectors like RT-DETR, custom classifiers, generative models) on large-scale, domain-specific datasets (like sports imagery and video) Generalized Object Detection: Develop and implement advanced computer vision models capable of identifying a wide array of visual elements (e.g., logos, brand assets, on-screen graphics) in diverse and challenging sports content, including those not seen during training LLM & GenAI Integration: Explore and implement solutions leveraging LLMs and Generative AI for tasks such as content summarization, insight generation, data augmentation, and model validation (e.g., using vision models to verify detections) System Implementation & Deployment: Build and deploy production-ready AI/ML pipelines, ensuring efficiency, scalability, and maintainability. This includes developing APIs and integrating models into broader Nielsen Sports platforms UI/UX for AI Tools: Guide or contribute to the development of internal tools and simple user interfaces (using frameworks like Streamlit, Gradio, or web stacks) to showcase model capabilities, facilitate data annotation, and allow for human-in-the-loop validation Research & Innovation: Stay at the forefront of advancements in computer vision, LLMs, and related AI fields. Evaluate and prototype new technologies and methodologies to drive innovation within Nielsen Sports Mentorship & Collaboration: Mentor junior engineers, share knowledge, and collaborate effectively with cross-functional teams including product managers, data scientists, and operations Performance Optimization: Optimize model performance for speed and accuracy, and ensure efficient use of computational resources (including cloud platforms like AWS, GCP, or Azure) Data Strategy: Contribute to data acquisition, preprocessing, and augmentation strategies to enhance model performance and generalization Required Qualifications: Bachelors of Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field 5+ years (for Principal / MTS-4) / 8+ years (for Senior Principal / MTS-5) of hands-on experience in developing and deploying AI/ML models, with a strong focus on Computer Vision Proven experience in training deep learning models for object detection (e.g., YOLO, Faster R-CNN, DETR variants like RT-DETR) on custom datasets Experience in finetuning LLMs like Llama 2/3, Mistral, or open-source models available on Hugging Face using libraries such as Hugging Face Transformers, PEFT, or specialized frameworks like Axolotl/Unsloth Proficiency in Python and deep learning frameworks such as PyTorch (preferred) or TensorFlow/Keras Demonstrable experience with Multi Modal Large Language Models (LLMs) and their application, including familiarity with transformer architectures and fine-tuning techniques Experience with developing simple UIs for model interaction or data annotation (e.g., using Streamlit, Gradio, Flask/Django) Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and lifecycle management (e.g., Docker, Kubernetes, Kubeflow, MLflow) Strong software engineering fundamentals, including code versioning (Git), testing, and CI/CD practices Excellent problem-solving skills and the ability to work with complex, large-scale datasets Strong communication and collaboration skills, with the ability to convey complex technical concepts to diverse audiences Full Stack Development experience in any one stack Preferred Qualifications / Bonus Skills: Experience with Generative AI vision models for tasks like image analysis, description, or validation Track record of publications in top-tier AI/ML/CV conferences or journals Experience working with sports data (broadcast feeds, social media imagery, sponsorship analytics) Proficiency in cloud computing platforms (AWS, GCP, Azure) and their AI/ML services Experience with video processing and analysis techniques Familiarity with data pipeline and distributed computing tools (e.g., Apache Spark, Kafka) Demonstrated ability to lead technical projects and mentor team members Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @ nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law. Show more Show less

Education: Bachelor’s or master’s in computer science, Software Engineering, or a related field (or equivalent practical experience). Hands-On ML/AI Experience: Proven record of deploying, fine-tuning, or integrating large-scale NLP models or other advanced ML solutions. Programming & Frameworks: Strong proficiency in Python (PyTorch or TensorFlow) and familiarity with MLOps tools (e.g., Airflow, MLflow, Docker). Security & Compliance: Understanding of data privacy frameworks, encryption, and secure data handling practices, especially for sensitive internal documents. DevOps Knowledge: Comfortable setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). Collaborative Mindset: Experience working cross-functionally with technical and non-technical teams; ability to clearly communicate complex AI concepts. Role Overview Collaborate with cross-functional teams to build AI-driven applications for improved productivity and reporting. Lead integrations with hosted AI solutions (ChatGPT, Claude, Grok) for immediate functionality without transmitting sensitive data while laying the groundwork for a robust in-house AI infrastructure. Develop and maintain on-premises large language model (LLM) solutions (e.g. Llama) to ensure data privacy and secure intellectual property. Key Responsibilities LLM Pipeline Ownership: Set up, fine-tune, and deploy on-prem LLMs; manage data ingestion, cleaning, and maintenance for domain-specific knowledge bases. Data Governance & Security: Assist our IT department to implement role-based access controls, encryption protocols, and best practices to protect sensitive engineering data. Infrastructure & Tooling: Oversee hardware/server configurations (or cloud alternatives) for AI workloads; evaluate resource usage and optimize model performance. Software Development: Build and maintain internal AI-driven applications and services (e.g., automated report generation, advanced analytics, RAG interfaces, as well as custom desktop applications). Integration & Automation: Collaborate with project managers and domain experts to automate routine deliverables (reports, proposals, calculations) and speed up existing workflows. Best Practices & Documentation: Define coding standards, maintain technical documentation, and champion CI/CD and DevOps practices for AI software. Team Support & Training: Provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and limiting model “hallucinations.” Performance Monitoring: Track AI system metrics (speed, accuracy, utilization) and implement updates or retraining as necessary. Job Types: Full-time, Permanent Pay: ₹80,000.00 - ₹90,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person Application Deadline: 30/06/2025 Expected Start Date: 30/06/2025

About the Role: Grade Level (for internal use): 12 Lead Agentic AI Developer Location: Gurgaon, Hyderabad and Bangalore Job Description: A Lead Agentic AI Developer will drive the design, development, and deployment of autonomous AI systems that enable intelligent, self-directed decision-making. Their day-to-day operations focus on advancing AI capabilities, leading teams, and ensuring ethical, scalable implementations. Responsibilities AI System Design and Development : Architect and build autonomous AI systems that integrate with enterprise workflows, cloud platforms, and LLM frameworks. Develop APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Team Leadership and Mentorship : Lead cross-functional teams of AI engineers, data scientists, and developers. Mentor junior staff in agentic AI principles, reinforcement learning, and ethical AI governance. Customization and Advancement : Optimize autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Fine-tune LLMs, multi-agent frameworks, and feedback loops to align with business goals. Ethical AI Governance : Monitor AI behavior, audit decision-making processes, and implement safeguards to ensure transparency, fairness, and compliance with regulatory standards. Innovation and Research : Spearhead R&D initiatives to advance agentic AI capabilities. Experiment with emerging frameworks (e.g.,Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems. Documentation and Thought Leadership : Publish technical white papers, case studies, and best practices for autonomous AI. Share insights at conferences and contribute to open-source AI communities. System Validation : Oversee rigorous testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation. Validate alignment with ethical and performance benchmarks. Stakeholder Leadership : Collaborate with executives, product teams, and compliance officers to align AI initiatives with strategic objectives. Advocate for AI-driven innovation across the organization. What We’re Looking For : REQUIRED SKILLS/QUALIFICATIONS Technical Expertise : 8+ years as a Senior AI Engineer , ML Architect , or AI Solutions Lead , with 5+ years focused on autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js . Hands-on experience with autonomous AI tools : LangChain, Autogen, CrewAI, or custom agentic frameworks. Proficiency in cloud platforms : AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI. Experience with MLOps pipelines (e.g., Kubeflow, MLflow) and scalable deployment of AI agents. Leadership : Proven track record of leading AI/ML teams, managing complex projects, and mentoring technical staff. Ethical AI : Familiarity with AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and bias mitigation techniques. Communication : Exceptional ability to translate technical AI concepts for non-technical stakeholders. Nice to have : Contributions to AI research (published papers, patents) or open-source AI projects (e.g., TensorFlow Agents, AutoGen). Experience with DevOps/MLOps tools: Kubeflow, MLflow, Docker, or Terraform. Expertise in NLP, computer vision, or graph-based AI systems. Familiarity with quantum computing or neuromorphic architectures for AI. 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. ----------------------------------------------------------- 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: 316524 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India

About the Role: Grade Level (for internal use): 13 Location: Gurgaon, Hyderabad and Bangalore Job Description: We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications: Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect , ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks : LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture : AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen: Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. 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. ----------------------------------------------------------- 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: 316525 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India

Overview: Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Pipelines. You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments. Responsibilities: Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Active contributor to code & development in projects and services Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption. Partner with ML engineers working on industrialization. Communicate with business stakeholders in the process of service design, training and knowledge transfer. Support large-scale experimentation and build data-driven models. Refine requirements into modelling problems. Influence product teams through data-based recommendations. Research in state-of-the-art methodologies. Create documentation for learnings and knowledge transfer. Create reusable packages or libraries. Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Leverage big data technologies to help process data and build scaled data pipelines (batch to real time) Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines Automate ML models deployments Qualifications: BE/B.Tech in Computer Science, Maths, technical fields. Overall 2-4 years of experience working as a Data Scientist. 2+ years’ experience building solutions in the commercial or in the supply chain space. 2+ years working in a team to deliver production level analytic solutions. Fluent in git (version control). Understanding of Jenkins, Docker are a plus. Fluent in SQL syntaxis. 2+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems. 2+ years’ experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Pyspark development. Data Science – Hands on experience and strong knowledge of building machine learning models – supervised and unsupervised models. Knowledge of Time series/Demand Forecast models is a plus Programming Skills – Hands-on experience in statistical programming languages like Python, Pyspark and database query languages like SQL Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Cloud (Azure) – Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool. Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities Experience with Agile methodology for team work and analytics ‘product’ creation. Experience in Reinforcement Learning is a plus. Experience in Simulation and Optimization problems in any space is a plus. Experience with Bayesian methods is a plus. Experience with Causal inference is a plus. Experience with NLP is a plus. Experience with Responsible AI is a plus. Experience with distributed machine learning is a plus Experience in DevOps, hands-on experience with one or more cloud service providers AWS, GCP, Azure(preferred) Model deployment experience is a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is preferred Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Stakeholder engagement-BU, Vendors. Experience building statistical models in the Retail or Supply chain space is a plus

About the Role: Grade Level (for internal use): 12 Lead Agentic AI Developer Location: Gurgaon, Hyderabad and Bangalore Job Description: A Lead Agentic AI Developer will drive the design, development, and deployment of autonomous AI systems that enable intelligent, self-directed decision-making. Their day-to-day operations focus on advancing AI capabilities, leading teams, and ensuring ethical, scalable implementations. Responsibilities AI System Design and Development : Architect and build autonomous AI systems that integrate with enterprise workflows, cloud platforms, and LLM frameworks. Develop APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Team Leadership and Mentorship : Lead cross-functional teams of AI engineers, data scientists, and developers. Mentor junior staff in agentic AI principles, reinforcement learning, and ethical AI governance. Customization and Advancement : Optimize autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Fine-tune LLMs, multi-agent frameworks, and feedback loops to align with business goals. Ethical AI Governance : Monitor AI behavior, audit decision-making processes, and implement safeguards to ensure transparency, fairness, and compliance with regulatory standards. Innovation and Research : Spearhead R&D initiatives to advance agentic AI capabilities. Experiment with emerging frameworks (e.g.,Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems. Documentation and Thought Leadership : Publish technical white papers, case studies, and best practices for autonomous AI. Share insights at conferences and contribute to open-source AI communities. System Validation : Oversee rigorous testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation. Validate alignment with ethical and performance benchmarks. Stakeholder Leadership : Collaborate with executives, product teams, and compliance officers to align AI initiatives with strategic objectives. Advocate for AI-driven innovation across the organization. What We’re Looking For : REQUIRED SKILLS/QUALIFICATIONS Technical Expertise : 8+ years as a Senior AI Engineer , ML Architect , or AI Solutions Lead , with 5+ years focused on autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js . Hands-on experience with autonomous AI tools : LangChain, Autogen, CrewAI, or custom agentic frameworks. Proficiency in cloud platforms : AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI. Experience with MLOps pipelines (e.g., Kubeflow, MLflow) and scalable deployment of AI agents. Leadership : Proven track record of leading AI/ML teams, managing complex projects, and mentoring technical staff. Ethical AI : Familiarity with AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and bias mitigation techniques. Communication : Exceptional ability to translate technical AI concepts for non-technical stakeholders. Nice to have : Contributions to AI research (published papers, patents) or open-source AI projects (e.g., TensorFlow Agents, AutoGen). Experience with DevOps/MLOps tools: Kubeflow, MLflow, Docker, or Terraform. Expertise in NLP, computer vision, or graph-based AI systems. Familiarity with quantum computing or neuromorphic architectures for AI. 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. ----------------------------------------------------------- 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: 316524 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India

About the Role: Grade Level (for internal use): 13 Location: Gurgaon, Hyderabad and Bangalore Job Description: We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications: Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect , ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks : LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture : AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen: Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. 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. ----------------------------------------------------------- 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: 316525 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Roles and Responsibilities: Lead the design, development, and implementation of AI/ML-based solutions across various product lines Collaborate with product managers, data engineers, and architects to translate business requirements into data science problems and solutions Take ownership of end-to-end AI/ML modules, from data processing to model development, testing, and deployment Provide technical leadership to a team of data scientists, ensuring high-quality outputs and adherence to best practices Conduct cutting-edge research and capability building across the latest Machine Learning, Deep Learning, and AI technologies Prepare technical documentation, including high-level and low-level design, requirement specifications, and white papers Evaluate and fine-tune models, ensuring they meet performance requirements and deliver insights that drive product improvements Production exposure to Large Language Models (LLM) and experience in implementing and optimizing LLM-based solutions Must-have Skills: 5-10 years of experience in Data Science and AI/ML product development, with a proven track record of leading technical teams Expertise in machine learning algorithms, Deep Learning models, Natural Language Processing, and Anomaly Detection Strong understanding of model lifecycle management, including model building, evaluation, and optimization Hands-on experience with Python and proficiency with frameworks like TensorFlow, Keras, PyTorch, etc Solid understanding of SQL, NoSQL databases, and data modeling with ElasticSearch experience Ability to manage multiple projects simultaneously in a fast-paced, agile environment Excellent problem-solving skills and communication abilities, particularly in documenting and presenting technical concepts Familiarity with Big Data frameworks such as Spark, Storm, Databricks, and Kafka Experience with container technologies like Docker and orchestration tools like Kubernetes, ECS, or EKS Optional (Good To Have) Skills: Experience with cloud-based machine learning platforms like AWS, Azure, or Google Cloud Experience with tools like MLFlow, KubeFlow, or similar for model tracking and orchestration Exposure to NoSQL databases such as MongoDB, Cassandra, Redis, and Cosmos DB, and familiarity with indexing mechanisms Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @ nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law. Show more Show less

Technical Expertise : (minimum 2 year relevant experience) ● Solid understanding of Generative AI models and Natural Language Processing (NLP) techniques, including Retrieval-Augmented Generation (RAG) systems, text generation, and embedding models. ● Exposure to Agentic AI concepts, multi-agent systems, and agent development using open-source frameworks like LangGraph and LangChain. ● Hands-on experience with modality-specific encoder models (text, image, audio) for multi-modal AI applications. ● Proficient in model fine-tuning, prompt engineering, using both open-source and proprietary LLMs. ● Experience with model quantization, optimization, and conversion techniques (FP32 to INT8, ONNX, TorchScript) for efficient deployment, including edge devices. ● Deep understanding of inference pipelines, batch processing, and real-time AI deployment on both CPU and GPU. ● Strong MLOps knowledge with experience in version control, reproducible pipelines, continuous training, and model monitoring using tools like MLflow, DVC, and Kubeflow. ● Practical experience with scikit-learn, TensorFlow, and PyTorch for experimentation and production-ready AI solutions. ● Familiarity with data preprocessing, standardization, and knowledge graphs (nice to have). ● Strong analytical mindset with a passion for building robust, scalable AI solutions. ● Skilled in Python, writing clean, modular, and efficient code. ● Proficient in RESTful API development using Flask, FastAPI, etc., with integrated AI/ML inference logic. ● Experience with MySQL, MongoDB, and vector databases like FAISS, Pinecone, or Weaviate for semantic search. ● Exposure to Neo4j and graph databases for relationship-driven insights. ● Hands-on with Docker and containerization to build scalable, reproducible, and portable AI services. ● Up-to-date with the latest in GenAI, LLMs, Agentic AI, and deployment strategies. ● Strong communication and collaboration skills, able to contribute in cross-functional and fast-paced environments. Bonus Skills ● Experience with cloud deployments on AWS, GCP, or Azure, including model deployment and model inferencing. ● Working knowledge of Computer Vision and real-time analytics using OpenCV, YOLO, and similar Job Type: Full-time Pay: From ₹300,000.00 per year Schedule: Day shift Experience: AI Engineer: 1 year (Required) Work Location: In person Expected Start Date: 23/06/2025

We are looking for a skilled and passionate AI/ML Engineer to join our team and help us build intelligent systems that leverage machine learning and artificial intelligence. You will design, develop, and deploy machine learning models, work closely with cross-functional teams, and contribute to cutting-edge solutions that solve real-world problems. Key Responsibilities: Design and implement machine learning models and algorithms for various use cases (e.g., prediction, classification, NLP, computer vision). Analyze and preprocess large datasets to build robust training pipelines. Conduct research to stay up to date with the latest AI/ML advancements and integrate relevant techniques into projects. Train, fine-tune, and optimize models for performance and scalability. Deploy models to production using tools such as Docker, Kubernetes, or cloud services (AWS, GCP, Azure). Collaborate with software engineers, data scientists, and product teams to integrate AI/ML solutions into applications. Monitor model performance in production and continuously iterate for improvements. Document design choices, code, and models for transparency and reproducibility. Preferred Qualifications: Knowledge in NLP, LLM and GenAI. Knowledge in deep learning architectures such as CNNs, RNNs, transformer models. Experience with NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). Background in deep learning architectures such as CNNs, RNNs, GANs, or transformer models. Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). Contributions to open-source AI/ML projects or publications in relevant conferences/journals. Required 3+ years experience. Work Mode : Onsite. Job Types: Full-time, Permanent Pay: ₹500,000.00 - ₹900,000.00 per year Benefits: Flexible schedule Health insurance Leave encashment Provident Fund Schedule: Day shift Fixed shift Monday to Friday Supplemental Pay: Performance bonus Work Location: In person

Job Description: Join our pioneering team at BuzzBoard, a recognized first-mover in enterprise generative AI, as a Team Lead of Generative AI and LLM. We've already deployed production GenAI systems generating thousands of posts and content pieces monthly across our ecosystem. You'll lead the charge in scaling our mature AI infrastructure while architecting next-generation applications. As a key leader in our Product Team, you'll orchestrate collaboration between Data Engineering, Software Engineering, and AI Operations teams while expanding our proven generative AI innovations. Key Responsibilities: Strategic Leadership & Vision Lead and mentor a team of GenAI engineers and researchers within our mature AI ecosystem Scale our proven production AI systems generating thousands of content pieces monthly across multiple business verticals Define generative AI strategy and roadmap building upon our established first-mover advantage Drive adoption of multimodal AI systems incorporating vision, audio, and text capabilities Contribute and own the GenAI governance frameworks and best practices Advanced AI Development Architect and scale sophisticated generative AI systems building upon our established multi-LLM infrastructure (GPT-4o, Claude Sonnet, Gemini, O1) Optimize our proven tech stack including LangChain, CrewAI, LangGraph, and vector databases (Chroma) Implement advanced RAG, fine-tuning, and prompt engineering across our existing model inventory Lead development of next-generation agentic AI systems with tool use, reasoning capabilities, and autonomous decision-making Enhance our multi-agent orchestration platforms and complex workflow automation Technology Leadership Drive adoption of agentic AI frameworks including LangGraph, CrewAI, AutoGen, and Microsoft Semantic Kernel Lead implementation of multi-agent orchestration platforms and autonomous decision-making systems Oversee vector databases (Pinecone, Weaviate, Chroma) and semantic search systems Lead integration of AI observability and monitoring tools (LangSmith, Weights & Biases, MLflow) Champion AI development platforms and low-code/no-code solutions Enterprise Integration & Scaling Scale our mature AI infrastructure supporting thousands of monthly content generations across multiple business verticals Enhance our proven MLOps and LLMOps practices for continuous model deployment and performance monitoring Drive technical collaboration for seamless AI integration into established production systems Optimize edge AI capabilities and multi-environment deployment strategies Enhance our performance tracking framework including regression testing, edit ratio tracking, and analytics integration Skills and Qualifications: Core Technical Expertise Deep expertise in generative AI systems, large language models, and transformer architectures with proven production experience Expert proficiency in our established tech stack: LangChain, CrewAI, LangGraph, AutoGen, and multi-LLM orchestration Hands-on experience with our model ecosystem: OpenAI GPT, Anthropic, Google, and vector databases Extensive experience with agentic AI frameworks and autonomous workflow orchestration in production environments Hands-on with programming skills in Python with experience in FastAPI, Streamlit, and modern web frameworks Expert-level understanding of prompt engineering, fine-tuning techniques, and model optimization at scale AI Architecture & Operations Experience with vector databases, embedding models, and semantic search implementations Proficiency in containerization (Docker, Kubernetes) and cloud-native AI deployments Knowledge of AI model serving platforms (vLLM, TensorRT-LLM, Ollama) and inference optimization Understanding of AI safety, alignment, and responsible AI development practices Technical Leadership (Individual Contributor Focus) Experience providing technical guidance to engineering teams in fast-paced environments Experience with AI product development lifecycle and technical go-to-market strategies Strong technical communication and ability to explain AI concepts to technical and non-technical audiences Knowledge of AI regulation landscape and compliance requirements Modern AI Ecosystem Familiarity with AI agent frameworks (LangGraph, CrewAI, Microsoft Semantic Kernel) - REQUIRED Experience with compound AI systems and multi-step reasoning architectures - REQUIRED Experience with multimodal AI systems and computer vision integration Understanding of federated learning and privacy-preserving AI techniques Knowledge of AI model evaluation frameworks and benchmarking methodologies Advanced Qualifications: Agentic AI Mastery (Required) Extensive hands-on experience building and deploying agentic AI systems in production environments Deep understanding of tool-calling, function-calling, and API integration within agent workflows Proven track record with multi-agent collaboration patterns and complex reasoning chains Expertise in agent memory systems, context management, and state persistence across interactions Industry Integration Experience scaling production GenAI systems with proven track record of generating thousands of content pieces monthly Knowledge of multi-LLM orchestration and model switching strategies for optimal performance and cost efficiency Understanding of content generation workflows across social media, marketing, and business communications Familiarity with performance monitoring frameworks including regression testing and analytics dashboard integration Research & Innovation Experience with AI model interpretability and explainable AI techniques Knowledge of quantum-classical hybrid AI approaches and emerging paradigms Technical Excellence Advanced degree in Computer Science, AI, or related field (preferred) Experience building and scaling AI teams in fast-paced environments (preferred) Experience with AI ethics committees and responsible AI governance (preferred) Proven ability to drive digital transformation through AI adoption (preferred) Lead the future of GenAI innovation at BuzzBoard, where your expertise will build upon our established success in production generative AI systems. Join a first-mover organization that has already proven the enterprise value of GenAI at scale, generating thousands of content pieces monthly. Your role as Team Lead of Generative AI and LLM will position you to expand our proven AI ecosystem while defining the next generation of agentic AI solutions that drive measurable business impact. Powered by JazzHR 12dkkTUOj7 Show more Show less

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are We are looking for a passionate and skilled Python, AI/ML Lead Engineer with 7+ years of experience to join our team. As a Python/AI Lead, you will oversee the development and implementation of machine learning models, AI-driven solutions, and data-driven products. You will guide a team of engineers and collaborate with cross-functional teams to ensure the timely and high-quality delivery of projects. If you thrive in a fast-paced environment and love solving complex problems using data and intelligent algorithms, we’d love to hear from you. What You’ll Do Lead the design, development, and deployment of Gen AI and machine learning solutions using Python. Provide technical guidance and mentorship to team members, ensuring code quality, best practices, and performance optimization. Collaborate with product managers, data scientists, and other stakeholders to define project requirements and objectives. Take ownership of the full software development lifecycle (SDLC), from design to deployment, maintenance, and optimization. Perform code reviews, write technical documentation, and maintain high standards of software quality. Stay up to date with the latest trends and advancements in AI, machine learning, and Python development. Identify and mitigate technical risks in projects while ensuring timely delivery. Foster a collaborative environment and promote knowledge sharing across the engineering team. What You’ll Need 7+ years of professional experience in Python development, with at least 2 years in a technical leadership role. Strong hands-on experience with AI/ML frameworks, Gen AI LLMs and libraries such as TensorFlow, Scikit-learn,or Keras. Python – Strong hands-on experience. Machine Learning – Practical knowledge of supervised, unsupervised, and deep learning techniques. Generative AI – Experience working with LLMs or similar GenAI technologies. API Development – RESTful APIs and integration of ML models into production services. Databases – Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, etc.). Good To Have Skills Cloud Platforms – Familiarity with AWS, Azure, or Google Cloud Platform (GCP). TypeScript/JavaScript – Frontend or full-stack exposure for ML product interfaces. Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, etc.) Exposure to containerization (Docker) and orchestration (Kubernetes). WHAT’S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability Show more Show less

Company Overview Pinnacle Infotech values inclusive growth in an agile, diverse environment. With 30+ years of global experience, 3,400+ experts completed 15,000+ projects across 43+ countries for 5,000+ clients. Join us for rapid advancement, cutting-edge training, and impactful global projects. Embrace E.A.R.T.H. values, celebrate uniqueness, and drive swift career growth with Pinnaclites! Job Title: MLOps Engineer Job Summary: As an MLOps Engineer, you will be responsible for building, deploying, and maintaining the infrastructure required for machine learning models and ETL data pipelines. You will work closely with data scientists, and software developers to streamline our machine learning operations, manage data workflows, and ensure that the ML solutions are scalable, reliable, and secure. Location- Durgapur/Jaipur/Madurai Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in MLOps, data engineering, or a similar role. Proficiency in programming languages such as Python, Spark, and SQL. Experience with ML model deployment frameworks and tools (e.g., MLflow). Hands-on experience with cloud platforms (AWS, Azure, GCP) and infrastructure management. Familiarity with containerization and orchestration tools (Docker, Kubernetes). Understanding of DevOps practices, CI/CD pipelines, and monitoring tools. Excellent problem-solving skills and the ability to work independently and as part of a team. Key Responsibilities: Data Engineering and Pipeline Management: Design, develop, optimize, and maintain ETL processes and data pipelines to collect, process, and store data from multiple sources. Ensure data quality, integrity, and consistency across various databases. Collaborate with data scientists to make data available in the right format and speed for machine learning. Implement and manage data security and privacy protocols as per industry standards. ML Operations and Deployment: Design, build, and optimize scalable and reliable ML deployment pipelines. Develop CI/CD pipelines for automated ML model training, testing, and deployment. Implement and manage containerization (Docker) and orchestration tools (e.g., Kubernetes) for ML workflows. Monitor and troubleshoot model performance and infrastructure, ensuring smooth operation in production environments. Infrastructure Management: Manage cloud infrastructure (AWS, GCP, Azure) to support data and ML operations. Optimize and scale ML and data workflows to handle large-scale datasets. Set up and manage monitoring tools for infrastructure and application performance. Collaboration and Best Practices: Work closely with data science, software development, and product teams to understand project needs and optimize model performance. Develop and document best practices, guidelines, and protocols for ML lifecycle management. Interested candidates, please share your resume at sunitas@pinnacleinfotech.com Show more Show less

Position: AI/ML Engineer (VFX Workflow & Infrastructure) Location: Hyderabad, India Role Overview The AI/ML Engineer will spearhead the development and integration of artificial intelligence and machine learning solutions into our VFX production pipeline. You’ll work closely with pipeline developers, production managers, and creative teams to reimagine workflows, automate repetitive tasks, and push the boundaries of innovation in photorealistic rendering, stylized animation, and other CGI processes. This role combines deep technical expertise with a strong understanding of the demands of a fast-paced VFX/animation studio. Key Responsibilities AI Strategy & Roadmap: Develop and maintain a strategic plan for implementing AI/ML across the VFX pipeline—covering data wrangling, rendering, asset management, animation, and post-production. Identify new approaches to innovate current workflows to increase efficiency and cut down on time. Algorithm & Model Development: Research, design, and implement ML models (e.g., computer vision, generative models, style transfer) that improve artist efficiency, production speed, enhance image quality, or enable new creative possibilities. Optimize models for performance on local GPU/CPU clusters or cloud-based infrastructures. Pipeline Integration & Automation: Collaborate with pipeline engineers to seamlessly integrate AI agents or tools into existing software stacks (e.g., Maya, Houdini, Nuke), ensuring minimal disruption to artists’ workflows. Develop automated solutions for tasks like rotoscoping, clean-up, crowd simulation, environment generation, or facial capture/animation. Infrastructure & Tooling: Architect and maintain robust data pipelines, ensuring the secure collection and organization of high-quality datasets for training AI models. Evaluate and deploy containerization/MLOps tools (Docker, Kubernetes, MLflow, etc.) for scalable model training, inference, and monitoring. Performance Optimization: Profile model performance, memory usage, and render times; implement optimizations in frameworks such as TensorFlow, PyTorch, or custom GPU pipelines. Work with DevOps/IT teams to configure and manage dedicated GPU farms or cloud compute resources. Research & Development: Stay updated with state-of-the-art ML/DL techniques, particularly in generative AI, computer vision, and real-time rendering. Introduce emerging methods (e.g., stable diffusion, large language models, neural rendering) to innovate new production techniques. Documentation & Reporting: Create clear technical documentation for AI solutions, ensuring maintainability and scalability. Present progress, insights, and ROI to executive leadership, project stakeholders, and cross-functional teams. Qualifications & Skills Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field. A PhD is a bonus but not mandatory. 5+ years of professional experience in applied machine learning or data science, with at least 2 years in a lead/managerial role. Previous experience in VFX, animation, gaming, or related entertainment industries is a bonus. Programming: Expert-level Python (C++ is a plus). ML Frameworks: Deep understanding of TensorFlow, PyTorch, scikit-learn, or similar libraries. Computer Vision & Generative Models: Familiarity with CNNs, GANs, autoencoders, stable diffusion, or neural radiance fields. Pipeline Tools: Experience with integration in VFX software (Maya, Houdini, Nuke) and plugin APIs.[Optional] DevOps & MLOps: Comfortable with containerization (Docker), orchestration (Kubernetes), CI/CD, and cloud platforms (AWS, Azure, GCP). Proven track record of translating production challenges into AI/ML solutions that deliver measurable efficiency gains or cost savings. Experience with model optimization (quantization, pruning) and GPU/CPU performance tuning. Collaboration: Excellent communication to bridge technical and creative teams, explaining complex concepts in clear, accessible language. Leadership: Ability to mentor junior engineers and foster a culture of experimentation and continuous learning. Agility: Adapts quickly to evolving project needs, production pipelines, and new AI techniques. A genuine interest in cinema, animation, or gaming—a plus if you have prior knowledge of the Baahubali IP or similar large-scale IPs. Creativity in applying AI to artistic challenges, from photorealistic digital humans to stylized animated sequences. What We Offer Impactful Role: Shape the future of VFX and animation filmmaking and leave a lasting mark on flagship studio projects. Career Growth: Lead a growing AI team, collaborate with top-tier VFX artists, and gain exposure to cutting-edge tech. Competitive Compensation: Salary, benefits, and potential for performance-based bonuses. Innovative Environment: Access to advanced hardware, robust R&D budget, and the opportunity to experiment with emerging AI trends. Show more Show less

Position Overview: ShyftLabs is seeking an experienced Databricks Architect to lead the design, development, and optimization of big data solutions using the Databricks Unified Analytics Platform. This role requires deep expertise in Apache Spark, SQL, Python, and cloud platforms (AWS/Azure/GCP). The ideal candidate will collaborate with cross-functional teams to architect scalable, high-performance data platforms and drive data-driven innovation. ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to accelerate business growth across various industries by focusing on creating value through innovation. Job Responsibilities Architect, design, and optimize big data and AI/ML solutions on the Databricks platform. Develop and implement highly scalable ETL pipelines for processing large datasets. Lead the adoption of Apache Spark for distributed data processing and real-time analytics. Define and enforce data governance, security policies, and compliance standards. Optimize data lakehouse architectures for performance, scalability, and cost-efficiency. Collaborate with data scientists, analysts, and engineers to enable AI/ML-driven insights. Oversee and troubleshoot Databricks clusters, jobs, and performance bottlenecks. Automate data workflows using CI/CD pipelines and infrastructure-as-code practices. Ensure data integrity, quality, and reliability across all data processes. Basic Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. 10+ years of hands-on experience in data engineering, with at least 5+ years in Databricks Architect and Apache Spark. Proficiency in SQL, Python, or Scala for data processing and analytics. Extensive experience with cloud platforms (AWS, Azure, or GCP) for data engineering. Strong knowledge of ETL frameworks, data lakes, and Delta Lake architecture. Hands-on experience with CI/CD tools and DevOps best practices. Familiarity with data security, compliance, and governance best practices. Strong problem-solving and analytical skills in a fast-paced environment. Preferred Qualifications: Databricks certifications (e.g., Databricks Certified Data Engineer, Spark Developer). Hands-on experience with MLflow, Feature Store, or Databricks SQL. Exposure to Kubernetes, Docker, and Terraform. Experience with streaming data architectures (Kafka, Kinesis, etc.). Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker). Prior experience working with retail, e-commerce, or ad-tech data platforms. We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources. Show more Show less

Role Overview: We are seeking an experienced DevOps Engineer with a strong background in managing AI-related operations and application development processes. The ideal candidate will have a deep understanding of DevOps practices, infrastructure automation, and the deployment and monitoring of AI/ML models in production environments. Key Responsibilities: Set up and maintain CI/CD pipelines (GitHub Actions, GitLab CI/CD, Jenkins) Infra provisioning with Terraform, CloudFormation, or Ansible Manage ML pipelines using Kubeflow, MLflow, Airflow, or Metaflow Deploy and manage containerized services using Docker and Kubernetes (EKS preferred) Design scalable, reliable systems on AWS (Auto Scaling, ELB, ECS/EKS, RDS, S3, CloudFront, etc.) Set up monitoring/logging with Prometheus, Grafana, CloudWatch, ELK, or DataDog Collaborate with data and backend teams for model deployment and lifecycle management Implement security best practices and drive incident response + RCA when needed Stay updated on new DevOps/MLOps tools to improve system efficiency Required Qualifications: 3–5+ years in DevOps or similar role Strong AWS experience — especially with scaling, HA design, and core services (EC2, EKS, RDS, S3) Good experience with CI/CD tools and Infrastructure as Code (Terraform, CloudFormation, Ansible) Hands-on with Docker, Kubernetes, and managing containerized workloads Experience deploying ML models in production environments Familiarity with monitoring and alerting tools (Prometheus, Grafana, ELK, etc.) Cloud and container security awareness Nice to Have: Experience with MLOps platforms (Kubeflow, MLflow, SageMaker, Vertex AI, Metaflow) Scripting in Python or Bash Experience with config management tools like Ansible, Chef, or Puppet Understanding of VPC, IAM, cost optimization, and fault-tolerant architecture About the Company: Griphic is founded by IIT Delhi engineers. Our vision is to enrich lives through technological innovation. We combine cutting-edge AI with hyper-realistic virtual experiences to solve problems and bring disruption in the industry. We have a dynamic team with engineers from IIT Delhi, AI/ML engineers, VR developers, and many more. Our startup is backed by the world’s leading design documentation firm, SKETS Studio, which has a strength of 700+ people and specializes in BIM, architecture, VR, and 3D visualization. Interested candidates should submit their resumes at jobs@griphic.com along with a brief cover letter and any relevant project examples or GitHub links. Show more Show less

Work Experience : 3+ years Salary: 21 LPA Location: Bengaluru Title : MLops Engineer Team Charter: The team in India comes with multi-disciplinary skillset, including but not limited to the following areas: Develop models and algorithms using Deep Learning and Computer Vision on the captured data to provide meaningful analysis to our customers. Some of the projects include – object detection, OCR, barcode scanning, stereovision, SLAM, 3D-reconstruction, action recognition etc. Develop integrated embedded systems for our drones – including embedded system platform development, camera and sensor integration, flight controller and motor control system development, etc. Architect and develop full stack software to interface between our solution and customer database and access – including database development, API development, UI/UX, storage, security and processing for data acquired by the drone. Integration and testing of various off the shelf sensors and other modules with drone and related software. Design algorithms related to autonomy and flight controls. Responsibilities: As a Machine Learning Ops (MLOps) engineer, you will be responsible for building and maintaining the next generation of Vimaan’s ML Platform and Infrastructure. MLOps will have a major contribution in making CV & ML offerings scalable across the company products. We are building all these data & model pipelines to scale Vimaan operations and MLOps Engineer will play a key role in enabling that. You will lead initiatives geared towards making the Computer Vision Engineers at Vimaan more productive. You will setup the infrastructure that powers the ML teams, thus simplifying the development and deployment cycles of ML models. You will help establish best practices for the ML pipeline and partner with other infrastructure ops teams to help champion them across the company. Build and maintain data pipelines - data ingestion, filtering, generating pre-populated annotations, etc. Build and maintain model pipelines - model monitoring, automated triggering of model (re)training, auto-deployment of models to producti on servers and edge devices. Own the cloud stack which comprises all ML resources. Establish standards and practices around MLOps, including governance, compliance, and data security. Collaborate on managing ML infrastructure costs. Qualifications: Deep quantitative/programming background with degree (Bachelors, Masters or Ph.D.) in a highly analytical discipline, like Statistics, Electrical,Electronics, Computer Science, Mathematics, Operations Research, etc. A minimum of 3 years of experience in managing machine learning projects end-to-end focused on MLOps. Experience with building RESTful APIs for monitoring build & production systems using automated monitoring of models and corresponding alarm tools. Experience with data versioning tools such as Data Version Control (DVC). Build and maintain data pipelines by using tools like Dagster, Airflow etc. Experience with containerizing and deploying ML models. Hands-on experience with autoML tools, experiment tracking, model management, version tracking & model training (MLflow, W&B, Neptune etc.), model hyperparameter optimization, model evaluation, and visualization (Tensorboard). Sound knowledge and experience with atleast one DL frameworks such as PyTorch, TensorFlow, Keras. Experience with container technologies (Docker, Kubernetes etc). Experience with cloud services. Working knowledge of SQL based databases. Hands on experience with Python scientific computing stack such as numpy, scipy, scikit-learn Familiarity with Linux and git. Detail oriented design, code debugging and problem-solving skills. Effective communication skills: discussing with peers and driving logic driven conclusions. Ability to perspicuously communicate complex technical/architectural problems and propose solutions for the same. How to stand out Prior experience in deploying ML & DL solutions as services Experience with multiple cloud services. Ability to collaborate effectively across functions in a fast-paced environment. Experience with technical documentation and presentation for effective dissemination of work. Engineering experience in distributed systems and data infrastructure. Show more Show less

Job Description Practice Lead – Generative AI Practitioner Location: Hyderabad Department: AI & Engineering Strategy Experience: 10+ Years Required: - Bachelor’s or master’s degree in computer science, Machine Learning, or a related field; PhD is a plus. - 10+ years of experience in AI/ML, with at least 3 years in Generative AI or foundation model development. - Proven leadership in building GenAI teams or practices at scale. - Hands-on expertise with LLMs (e.g., GPT, LLaMA, Claude), vector databases, LangChain, and orchestration frameworks. - Strong understanding of prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and model evaluation. Preferred: - Experience in building GenAI Centers of Excellence or technical communities of practice. - Familiarity with LLMOps tools (e.g., Weights & Biases, MLflow, TruLens, Guardrails AI). - Certifications in cloud AI/ML platforms (AWS/GCP/Azure). - Recognized thought leadership in GenAI (e.g., speaking engagements, publications, OSS contributions). Show more Show less

Education: Bachelor’s or master’s in computer science, Software Engineering, or a related field (or equivalent practical experience). Hands-On ML/AI Experience: Proven record of deploying, fine-tuning, or integrating large-scale NLP models or other advanced ML solutions. Programming & Frameworks: Strong proficiency in Python (PyTorch or TensorFlow) and familiarity with MLOps tools (e.g., Airflow, MLflow, Docker). Security & Compliance: Understanding of data privacy frameworks, encryption, and secure data handling practices, especially for sensitive internal documents. DevOps Knowledge: Comfortable setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). Collaborative Mindset: Experience working cross-functionally with technical and non-technical teams; ability to clearly communicate complex AI concepts. Role Overview Collaborate with cross-functional teams to build AI-driven applications for improved productivity and reporting. Lead integrations with hosted AI solutions (ChatGPT, Claude, Grok) for immediate functionality without transmitting sensitive data while laying the groundwork for a robust in-house AI infrastructure. Develop and maintain on-premises large language model (LLM) solutions (e.g. Llama) to ensure data privacy and secure intellectual property. Key Responsibilities LLM Pipeline Ownership: Set up, fine-tune, and deploy on-prem LLMs; manage data ingestion, cleaning, and maintenance for domain-specific knowledge bases. Data Governance & Security: Assist our IT department to implement role-based access controls, encryption protocols, and best practices to protect sensitive engineering data. Infrastructure & Tooling: Oversee hardware/server configurations (or cloud alternatives) for AI workloads; evaluate resource usage and optimize model performance. Software Development: Build and maintain internal AI-driven applications and services (e.g., automated report generation, advanced analytics, RAG interfaces, as well as custom desktop applications). Integration & Automation: Collaborate with project managers and domain experts to automate routine deliverables (reports, proposals, calculations) and speed up existing workflows. Best Practices & Documentation: Define coding standards, maintain technical documentation, and champion CI/CD and DevOps practices for AI software. Team Support & Training: Provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and limiting model “hallucinations.” Performance Monitoring: Track AI system metrics (speed, accuracy, utilization) and implement updates or retraining as necessary. Job Types: Full-time, Permanent Pay: ₹80,000.00 - ₹90,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person Application Deadline: 30/06/2025 Expected Start Date: 30/06/2025

Develop and implement AI and machine learning strategies for several healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively 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 Qualifications - External - Undergraduate degree or equivalent experience. •5+ years of experience working with Python, AI •4+ years of experience with SQL Server, MYSQL, Oracle or other comparable RDMS database system •2+ years of experience with APIs / micro-services •2+ years of experience with CI/CD tools like Jenkins, GitHub Actions •1+ years of experience with code scanning and security tools for code vulnerability, code quality, secret scanning, penetration testing and threat modeling Preferred Qualifications: •Bachelor’s degree in computer science or related field •Experience with unit testing frameworks •Experience with version control systems like Git/GitHub •Proven ability to do POC on emerging tech-stack •Experience with Linux or Unix platform •Experience with RabbitMQ •Experience with Redis •Proven ability to independently troubleshoot problems and document RCAs •Experience with event steaming platforms such as Kafka Show more Show less