1552 Sagemaker Jobs - Page 16

A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. As part of our Analytics and Insights Consumption team, you’ll analyze data to drive useful insights for clients to address core business issues or to drive strategic outcomes. You'll use visualization, statistical and analytics models, AI/ML techniques, Modelops and other techniques to develop these insights. Years of Experience: Candidates with 4+ years of hands on experience Must Have Internal & External stakeholder management Familiarity with the CCaaS domain, CCaaS Application Development , contact center solution design & presales consulting. In-depth knowledge of CCaaS platforms like MS DCCP, Amazon Connect, NICECXOne, Genesys Cloud , Cisco Webex CC, Cisco HCS, UCCE/PCCE etc., including their architecture, functionalities, and application development, integration capabilities Governance & communication skills Hands-on configuration of Gen AI, LLM to be built on top of CCaaS platforms/Domain (MS DCCP, Amazon Connect, Genesys Cloud/NICE CX) includes, Develop and implement generative AI models to enhance customer interactions, including chatbots, virtual agents, and automated response systems. Speech scientist & speech, conversational fine-tuning (grammar & pattern analysis) Collaborate with stakeholders to identify business needs and define AI-driven solutions that improve customer experiences. Analyze existing customer service processes and workflows to identify areas for AI integration and optimization. Create and maintain documentation for AI solutions, including design specifications and user guides. Monitor and evaluate the performance of AI models, making adjustments as necessary to improve accuracy and effectiveness. Stay updated on the latest advancements in AI technologies and their applications in customer service and contact centers. Conduct training sessions for team members and stakeholders on the use and benefits of AI technologies in the contact center. Understanding of the fundamental ingredients of enterprise integration including interface definitions and contracts; REST APIs or SOAP web services; SQL,MY SQL, Oracle , PostgreSQL , Dynamo DB, S3, RDS Provide effective real time demonstrations of CCaaS & AI (Bots) platforms High proficiency in defining top notch customer facing slides/presentations Gen AI,LLM platforms MUST have technologies includes Copilot, Copilot Studio, Amazon Bedrock, Amazon Titan, Sagemaker, Azure OpenAI, Azure AI Services, Google Vertex AI, Gemini AI. Proficiency in data visualization tools like Tableau, Power BI, Quicksight and others Nice To Have Experience in CPaaS platforms (Twilio, Infobip) for synergies between Communication Platform As A Service & Contact Center As a Service Understanding of cloud platforms (e.g., AWS, Azure, Google Cloud) and their services for scalable data storage, processing, and analytics Work on high velocity Presales solution consulting engagements (RFP, RFI, RFQ) Define industry specific use cases (BFS & I, Telecom, Retail, Manlog etc) Work on high volume presales consulting engagements including solution design document definition, commercial construct (CCaaS) Defining Business Case

Company Profile Flentas helps enterprises leverage the full potential of the Cloud with the help of consulting and implementation practice. As an organization, Flentas has the technology expertise and experience to drive large digital transformation projects and scale cloud operations. Flentas serves clients globally of all shapes and sizes with a strong and passionate team of experienced Solution Architects and Technology Enthusiasts. Job Title: Generative AI Specialist Job Location: Pune. Job Brief We are seeking a skilled Generative AI Specialist with a strong background in implementing and optimizing cutting-edge AI solutions. The ideal candidate will have expertise in LangChain, LangGraph, and agentic frameworks, with hands-on experience in Python and cloud-based AI services like AWS Bedrock and SageMaker. Experience with fine-tuning models is a plus. Join our dynamic team to develop, deploy, and enhance AI-driven applications. Key Responsibilities Design, develop, and implement AI solutions using LangChain, LangGraph, and agentic frameworks. Develop and maintain scalable AI models leveraging AWS Bedrock and SageMaker. Build and deploy AI-driven agents capable of autonomous decision-making and task execution. Optimize machine learning pipelines and workflows for production environments. Collaborate with cross-functional teams to understand project requirements and deliver innovative AI solutions. Conduct fine-tuning and customization of generative AI models (good to have). Monitor, evaluate, and improve the performance of AI systems. Stay updated on the latest advancements in generative AI and related technologies. Required Skills Proficiency in LangChain, LangGraph, and agentic frameworks. Strong programming skills in Python. Experience with AWS Bedrock and SageMaker for AI model deployment. Knowledge of AI and ML workflows, including model optimization and scalability. Understanding of APIs, data integration, and AI-driven task automation. Preferred Skills (Good To Have) Experience with fine-tuning generative AI models. Familiarity with cloud-based architecture and services beyond AWS (e.g., GCP, Azure). Knowledge of advanced NLP and transformer-based architectures. Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field. 3-5 years of hands-on experience in AI development, with a focus on generative models. Demonstrated experience in deploying AI solutions in a cloud environment.

We are looking for a highly motivated and enthusiastic Senior Data Scientist with 5-8 years of experience to join our dynamic team. The ideal candidate should have a strong background in AI/ML analytics and a passion for utilizing data to drive business insights and innovation. Your main responsibilities will include developing and implementing machine learning models and algorithms, collaborating with project stakeholders to understand requirements and deliverables, analyzing and interpreting complex data sets using statistical and machine learning techniques, staying updated with the latest advancements in AI/ML technologies, and supporting various AI/ML initiatives by working with cross-functional teams. To qualify for this role, you should have a Bachelor's degree in Computer Science, Data Science, or a related field, along with a strong understanding of machine learning, deep learning, and Generative AI concepts. Preferred skills for this position include experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, and Deep Learning stack using Python. Additionally, expertise in cloud infrastructure for AI/ML on AWS (Sagemaker, Quicksight, Athena, Glue), building secure data ingestion pipelines for unstructured data, proficiency in Python, TypeScript, NodeJS, ReactJS, data visualization tools, deep learning frameworks, version control systems, and Generative AI/LLM based development is desired. Good to have skills include knowledge and experience in building knowledge graphs in production and an understanding of multi-agent systems and their applications in complex problem-solving scenarios. Pentair is an Equal Opportunity Employer, valuing cross-cultural insight and competence for ongoing success, with a belief that a diverse workforce enhances perspectives and ideas for continuous improvement.,

Job Summary We are looking for a visionary Senior AVP – Generative AI Lead to spearhead our Generative AI initiatives. In this senior leadership role, you will design and execute cutting-edge AI strategies leveraging generative models to drive innovation, optimize business processes, and create new AI-driven products. You will lead a cross-functional team of AI researchers, engineers, and data scientists to develop scalable generative AI solutions that align with organizational goals. Key Responsibilities Lead the development and deployment of generative AI models (e.g., GPT, diffusion models, transformers) across various business units. Define the AI strategy focusing on generative models to enhance product offerings, customer experience, and operational efficiency. Collaborate with business leaders and technology teams to identify high-impact use cases and translate them into AI solutions. Oversee research and experimentation to stay ahead of advancements in generative AI and related technologies. Manage, mentor, and grow a high-performing team of AI specialists, fostering innovation and technical excellence. Ensure ethical AI practices, data privacy, and compliance in all generative AI projects. Drive AI infrastructure development and integration with existing technology platforms. Present technical insights and strategic recommendations to C-suite executives and stakeholders. Build partnerships with external AI vendors, academic institutions, and industry consortia. Qualifications: Master’s or PhD in Computer Science, AI, Machine Learning, or related technical field. 10+ years of experience in AI/ML, with at least 5 years focused on generative AI technologies. Proven track record in leading AI teams and delivering large-scale generative AI projects. Deep knowledge of generative AI architectures such as transformers, GANs, VAEs, diffusion models, etc. Strong programming skills in Python, TensorFlow, PyTorch, or similar frameworks. Experience with cloud AI services (AWS Sagemaker, Azure AI, Google AI) and scalable deployment. Strong business acumen and ability to translate AI capabilities into measurable business outcomes. Excellent leadership, communication, and stakeholder management skills. Understanding of AI ethics, fairness, and regulatory considerations. Preferred Skills: Experience in NLP, computer vision, or multimodal generative models. Familiarity with large language models (LLMs) like GPT-4, PaLM, or similar. Background in product innovation or AI-driven transformation initiatives. Exposure to Agile and DevOps practices for AI/ML workflows.

You should have expert-level proficiency in Python and Python frameworks or Java. You must have hands-on experience with AWS Development, PySpark, Lambdas, Cloud Watch (Alerts), SNS, SQS, CloudFormation, Docker, ECS, Fargate, and ECR. Deep experience with key AWS services like Compute (PySpark, Lambda, ECS), Storage (S3), Databases (DynamoDB, Snowflake), Networking (VPC, 53, CloudFront, API Gateway), DevOps/CI-CD (CloudFormation, CDK), Security (IAM, KMS, Secrets Manager), Monitoring (CloudWatch, X-Ray, CloudTrail), and NoSQL Databases like Cassandra, PostGreSQL is required. You should have very strong hands-on knowledge of using Python for integrations between systems through different data formats. Expertise in deploying and maintaining applications in AWS, along with hands-on experience in Kinesis streams and Auto-scaling, is essential. Designing and implementing distributed systems and microservices, and following best practices for scalability, high availability, and fault tolerance are key responsibilities. Strong problem-solving and debugging skills are necessary for this role. You should also have the ability to lead technical discussions and mentor junior engineers. Excellent written and verbal communication skills are a must. Comfort working in agile teams with modern development practices and collaborating with business and other teams to understand business requirements and work on project deliverables is expected. Participation in requirements gathering, understanding, designing a solution based on available framework and code, and experience with data engineering tools or ML platforms (e.g., Pandas, Airflow, SageMaker) are required. An AWS certification such as AWS Certified Solutions Architect or Developer is preferred. This position is based in multiple locations including Indore, Mumbai, Noida, Bangalore, Chennai in India. Qualifications: - Bachelor's degree or foreign equivalent required from an accredited institution. Consideration will be given to three years of progressive experience in the specialty in lieu of every year of education. - At least 8+ years of Information Technology experience.,

Inviting applications for the role of Principal Consultant -MLOps Engineer! In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments. Responsibilities . Develop and maintain CI/CD pipelines for AI/GenAI models on AWS using GitHub Actions and CodePipeline. (Not Limited to) . Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc) . Any cloud platform- Azure or AWS . Package and deploy AI/GenAI models on (SageMaker, Lambda, API Gateway). . Write Python scripts for automation, deployment, and monitoring. . Engaging in the design, development and maintenance of data pipelines for various AI use cases . Active contribution to key deliverables as part of an agile development team . Set up model monitoring, logging, and alerting (e.g., drift, latency, failures). . Ensure model governance, versioning, and traceability across environments. . Collaborating with others to source, analyse, test and deploy data processes . Experience in GenAI project Qualifications we seek in you! Minimum Qualifications experience with MLOps practices. . Degree/qualification in Computer Science or a related field, or equivalent work experience . Experience developing, testing, and deploying data pipelines Strong Python programming skills. Hands-on experience in deploying 2 - 3 AI/GenAI models in AWS. Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases. . Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills . Experience with Docker-based deployments. . Exposure to model monitoring tools (Evidently, CloudWatch). . Familiarity with RAG stacks or fine-tuning LLMs. . Understanding of GitOps practices. . Knowledge of governance and compliance policies, standards, and procedures

Description We have an outstanding opportunity for an expert AI and Data Cloud Solutions Engineer to work with our trailblazing customers in crafting ground-breaking customer engagement roadmaps demonstrating the Salesforce applications, platform across the machine learning and LLM/GPT domains in India! The successful applicant will have a track record in driving business outcomes through technology solutions, with experience in engaging at the C-level with Business and Technology groups. Responsibilities Primary pre-sales technical authority for all aspects of AI usage within the Salesforce product portfolio - existing Einstein ML based capabilities and new (2023) generative AI Majority of time (60%+) will be customer/external facing Evangelisation of Salesforce AI capabilities Assessing customer requirements and use cases and aligning to these capabilities Solution proposals, working with Architects and wider Solution Engineer (SE) teams Preferred Qualifications expertise in an AI related subject (ML, deep learning, NLP etc.) Familiar with technologies such as OpenAI, Google Vertex, Amazon Sagemaker, Snowflake, Databricks etc Required Qualifications: Experience will be evaluated based on the core proficiencies of the role. 4+ years working directly in the commercial technology space with AI products and solutions. Data knowledge - Data science, Data lakes and warehouses, ETL, ELT, data quality AI knowledge - application of algorithms and models to solve business problems (ML, LLMs, GPT) 10+ years working in a sales, pre-sales, consulting or related function in a commercial software company Strong focus and experience in pre-sales or implementation is required. Experience in demonstrating Customer engagement solution, understand and drive use cases, customer journeys, ability to draw ‘Day in life of’ across different LOBs. Business Analysis/ Business case/return on investment construction. Demonstrable experience in presenting and communicating complex concepts to large audiences A broad understanding of and ability to articulate the benefits of CRM, Sales, Service and Marketing cloud offerings Strong verbal and written communications skills with a focus on needs analysis, positioning, business justification, and closing techniques. Continuous learning demeanor with a demonstrated history of self enablement and advancement in both technology and behavioural areas. Building reference models/ideas/approaches for inclusion of GPT based products within wider Salesforce solution architectures, especially involving Data Cloud Alignment with customer security and privacy teams on trust capabilities and values of our solution(s) Presenting at multiple customer events from single account sessions through to major strategic events (World Tour, Dreamforce) Representing Salesforce at other events (subject to PM approval) Sales and SE organisation education and enablement e.g. roadmap - all roles across all product areas Bridge/primary contact point to product management Provide thought leadership in how large enterprise organisation can drive customer success through digital transformation. Ability to uncover the challenges and issues a business is facing by running successful and targeted discovery sessions and workshops. Be an innovator who can build new solutions using out-of-the-box thinking. Demonstrate business value of our AI solutions to business using solution presentations, demonstrations and prototypes. Build roadmaps that clearly articulate how partners can implement and accept solutions to move from current to future state. Deliver functional and technical responses to RFPs/RFIs. Work as an excellent teammate by chipping in, learning and sharing new knowledge. Demonstrate a conceptual knowledge of how to integrate cloud applications to existing business applications and technology. Lead multiple customer engagements concurrently. Be self-motivated, flexible, and take initiative.|

As an AI Architect, you will design and deploy scalable, autonomous AI systems, ensuring seamless integration with cloud platforms and enterprise workflows. You will lead AI strategy, evaluate emerging frameworks, and optimize AI models for real-world applications while driving innovation in agentic AI. Key Responsibilities AI System Design: Architect scalable, autonomous AI/ML systems, including APIs, agents, and pipelines for dynamic decision-making. Technical Leadership: Guide AI engineers and data scientists in implementing advanced architectures (LLMs, multi-agent frameworks). Cloud & Framework Expertise: Deploy AI solutions on AWS SageMaker, Azure ML, or Vertex AI; leverage tools like LangChain, AutoGPT, or Autogen. Optimization & Customization: Fine-tune LLMs and AI models for domain-specific tasks (real-time analytics, adaptive automation). Innovation & R&D: Prototype emerging AI architectures (neuro-symbolic systems, self-improving agents) for production viability. System Validation: Ensure robustness via stress testing, bias mitigation, and compliance with ethical AI standards. Stakeholder Collaboration: Align AI initiatives with business goals and advocate for AI-driven innovation. Required Skills & Qualifications Minimum 6 years of hands-on experience in AI architecture, cloud platforms (AWS/Azure/GCP), and LLM frameworks. Proficiency in Python, TensorFlow/PyTorch, and AI deployment tools (SageMaker, Vertex AI). Strong background in autonomous agents, multi-agent systems, and AI optimization. Experience with LangChain, AutoGPT, or similar frameworks is a plus. Ability to translate research into production-ready architectures. Excellent communication and leadership skills. About Us CoinFantasy is a revolutionary Play to Invest platform that transforms the world of investing into an engaging and intuitive gaming experience. Our platform offers multiple game categories, allowing users to explore the end-to-end investment journey in a risk-free sandbox environment. Building on this innovative foundation, we are now pioneering a groundbreaking decentralized protocol set to redefine the AI landscape. Join us in shaping the future of finance and technology! Website: Benefits Competitive salary and performance incentives. Be part of the Core Team in a fast-growing, innovative company. Fulfilling & challenging work with real impact on the product. Unlimited growth opportunities – professionally and personally.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible. As an ML Engineer, you’ll be provided with all opportunities for development and growth. Let's work together to build a better future for everyone! Requirements: Comfortable with standard ML algorithms and underlying math. Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems AWS Bedrock experience strongly preferred Practical experience with solving classification and regression tasks in general, feature engineering. Practical experience with ML models in production. Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts). Python expertise, Docker. English level - strong Intermediate. Excellent communication and problem-solving skills. Will be a plus: Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda). Practical experience with deep learning models. Experience with taxonomies or ontologies. Practical experience with machine learning pipelines to orchestrate complicated workflows. Practical experience with Spark/Dask, Great Expectations. Responsibilities: Create ML models from scratch or improve existing models. Collaborate with the engineering team, data scientists, and product managers on production models. Develop experimentation roadmap. Set up a reproducible experimentation environment and maintain experimentation pipelines. Monitor and maintain ML models in production to ensure optimal performance. Write clear and comprehensive documentation for ML models, processes, and pipelines. Stay updated with the latest developments in ML and AI and propose innovative solutions.

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses. We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale. Responsibilities: Leadership & Management Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment; Drive the roadmap for machine learning projects aligned with business goals; Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery. Machine Learning & LLM Expertise Design, develop, and fine-tune LLMs and other machine learning models to solve business problems; Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction; Stay ahead of advancements in LLMs and apply emerging technologies; Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML. AWS Cloud Expertise Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.); Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS; Ensure best practices in security, monitoring, and compliance within the cloud infrastructure. Technical Execution Oversee the entire ML lifecycle, from research and experimentation to production and maintenance; Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows; Debug, troubleshoot, and optimize production ML models for performance. Team Development & Communication Conduct regular code reviews and ensure engineering standards are upheld; Facilitate professional growth and learning for the team through continuous feedback and guidance; Communicate progress, challenges, and solutions to stakeholders and senior leadership. Qualifications: Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models); Strong expertise in AWS Cloud Services; Strong experience in ML/AI, including at least 2 years in a leadership role; Hands-on experience with Python, TensorFlow/PyTorch, and model optimization; Familiarity with MLOps tools and best practices; Excellent problem-solving and decision-making abilities; Strong communication skills and the ability to lead cross-functional teams; Passion for mentoring and developing engineers.

Job Description Change the world. Love your job. Texas Instruments is seeking experienced Data Scientist to join our team. As the Data Scientist in TI's Demand Analytics team, you will play a pivotal role in shaping and executing our demand planning and inventory buffer strategies for the company. You will be working side by side with a team of highly technical professionals that will consists of application developers, system architects, data scientists and data engineers. This role will be responsible for solving complex business problems through innovative solutions that deliver tangible business value. This position requires a technical leader with a strong technical background in AI/ML, simulation solutions, strategic thinking, and a passion for innovation through data.This team is responsible for:portfolio management for demand forecasting algorithms, generation of inventory buffer targets, segmentation of TI's products and simulation/validation frameworks, defining specs/reference architectures to best achieve business outcomes and ensuring security and interoperability between capabilities. Roles And Duties Stakeholder engagement: Work collaboratively and strategically with stakeholder groups to achieve TI business strategy and goals Communicate complex technical concepts and influence final business outcomes with stakeholders effectively Partner with cross-functional teams to identify and prioritize actionable, high-impact insights across a variety of core business areas Technology and platforms: Build simple, scalable and modular technology stacks using modern technologies and software engineering principles. Simulate real world scenarios with various models and approaches to determine best fit of algorithms by varying the inputs across hundreds to thousands of variables Research, experiment and implement new approaches and models that flex with the business strategy transformations Leads data acquisition and engineering efforts Develops and applies machine learning, AI and data engineering framework Solutions, writes and debugs code for complex development projects Oversees, evaluates and determines the best modeling techniques for various scenarios letting the data drive the conversation Qualifications Minimum requirements: MS or PhD in a quantitative field (e.g., Computer Science, Statistics, Engineering, Mathematics) or equivalent practical experience. 8+ years of professional experience in data science or a related role. 5+ years of hands-on experience developing and deploying time series forecasting models in a professional setting. Demonstrated experience in the supply chain domain (e.g., Semiconductor, Retail, CPG, Pharmaceutical), with a deep understanding of concepts like demand forecasting, S&OP, or inventory management. Expert-level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, Statsmodels) and forecasting packages (e.g., Prophet, PyTorch Forecasting). Proven experience taking machine learning models from prototype to production, including knowledge of CI/CD and model monitoring. Preferred Qualifications Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes). Practical experience with cloud data science platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform). Familiarity with advanced forecasting techniques such as probabilistic forecasting, causal inference, or using Transformers for time series. Experience applying NLP to extract features from unstructured text to enhance forecasting models. Strong SQL skills and experience working with large-scale data warehousing solutions (e.g., Snowflake, BigQuery, Redshift). About Us Why TI? Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics. We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us. About Texas Instruments Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, personal electronics, communications equipment and enterprise systems. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com . Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. If you are interested in this position, please apply to this requisition. About The Team TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.

Role Overview Intertec Systems is seeking a visionary and execution-focused AI Practice Lead to head our AI initiatives across all lines of business— Digital, Managed Services, Cloud, EAM, Cybersecurity, and Microsoft solutions . This role will own the charter to define, build, and scale innovative AI use cases leveraging Machine Learning (ML), Computer Vision, Agentic AI, and Gen AI applications for: Client solutions (presales, PoCs, proposals) Internal business transformation Product roadmap acceleration The ideal candidate will be an expert hands-on AI engineer who can lead with both strategy and execution. This individual will lead the AI Center of Excellence (CoE) and work closely with Business Units, Technology Teams, and Clients. Key Responsibilities Strategy & Leadership Define and execute the vision and roadmap for AI adoption at Intertec across functions Lead the AI CoE and drive cross-functional collaboration with presales, delivery, product, and marketing teams Evaluate and prioritize AI use cases based on business impact and feasibility Solution Development & Presales Partner with sales and account teams to ideate and propose AI solutions in RFPs and client engagements Build PoCs, reference architectures, and solution accelerators using ML, Computer Vision, NLP, and Generative AI Identify AI opportunities with business outcomes across verticals like Government, Healthcare, Utilities, BFSI, and Real Estate Use Case Design & Development Own delivery of all active and upcoming AI use cases across Intertec’s client and internal platforms Drive implementation of Agentic AI (LLM-based task automation), multi-agent frameworks (e.g., CrewAI, LangGraph), and intelligent workflows Innovation & R&D Evaluate emerging AI technologies, LLMs, vector databases, and open-source models for product or customer requirements Pilot AI use cases internally (finance automation, talent intelligence, project risk prediction, etc.) Scale successfully piloted AI solutions within the organization Keep the organization at the forefront of GenAI, multi-modal AI, and enterprise AI trends Create a catalogue of resuable AI assets to be monetized by the company Governance & Enablement Define best practices, MLOps standards, data governance frameworks Train and upskill teams in AI tooling and architecture Ensure responsible AI practices, ethical design, and regulatory compliance Required Skills & Experience Must-Have Skills 7+ years in technology or consulting, with 4+ years in AI/ML Strong experience in AI presales and solution architecture (client-facing) Expert-level hands-on coding and prototyping experience Hands-on proficiency in: ML frameworks (TensorFlow, PyTorch, scikit-learn) Computer Vision (YOLO, OpenCV, segmentation models) Agentic AI tools (LangChain, CrewAI, AutoGen, RAG, LlamaIndex) Proven success building AI/ML PoCs, solutions, or products from scratch Familiar with vector databases, RAG architecture, prompt engineering, and LLM orchestration Knowledge of MLOps and deployment pipelines (MLflow, Kubeflow, Azure ML, Sagemaker) Excellent communication skills with the ability to influence both technical and non-technical stakeholders Strong understanding of cloud and infrastructure requirements for AI workloads , including: GPU types and capacity planning (e.g., A100, H100, T4) AI-optimized storage and high-throughput systems Deployment environments (Docker, Kubernetes, VM instances) Cost/performance analysis across Azure, AWS, GCP MLOps tools and scalable model deployment architectures Preferred/Bonus Experience leading AI practices in mid-sized or regional IT services companies Exposure to AI compliance and Responsible AI frameworks Tools & Technologies ML & CV : PyTorch, TensorFlow, scikit-learn, OpenCV, YOLO, Detectron2 LLMs & Agents : OpenAI, Anthropic, LangChain, CrewAI, LlamaIndex, Haystack Deployment : Azure AI, AWS Sagemaker, Vertex AI, Docker, Kubernetes Data & Ops : MLflow, Airflow, Hugging Face, Weights & Biases Vector DBs : FAISS, Pinecone, Chroma, Qdrant What You’ll Influence Shape the AI GTM strategy for Intertec Elevate client conversations from solutioning to innovation Help Intertec become an AI-first systems integrator

The AI Presales Consultant will be responsible for bridging the gap between technical expertise in Artificial Intelligence (AI) and business requirements of our international prospects. This individual will engage directly with clients, identifying industry-specific use cases for Generative AI, designing tailored solutions, collaborating with AI engineering teams, and developing compelling proposals that clearly articulate business value and technical feasibility. Key Responsibilities: • Conduct industry-specific research to identify relevant AI and Generative AI use cases that solve client business challenges. • Assess and differentiate between viable AI solutions and overly complex or ambitious use cases, providing practical and implementable recommendations. • Collaborate closely with AI Engineers and data science teams to design tailored AI solutions, estimate project efforts, and translate these into comprehensive proposals. • Develop detailed user flows, workflow diagrams, and solution architecture documents to ensure proposals clearly represent complete, end-to-end solutions. • Lead client-facing demonstrations, proof-of-concept (PoC) presentations, and actively support sales pitches by showcasing the business value of proposed AI solutions. • Maintain strong client relationships, ensuring a clear understanding of client objectives and effectively positioning AI solutions as strategic business enablers. • Continuously stay updated with the latest AI and Generative AI trends, platforms, and frameworks to ensure innovative and relevant solutioning. Qualifications and Skills: • Bachelor’s Degree in Computer Science, Engineering, IT, or related field; advanced degrees (MBA or Master’s in technical fields) preferred. • 4–7 years of experience in AI presales, solutions consulting, or business analysis roles, preferably within IT services or consulting organizations. • Demonstrable understanding of core AI and Generative AI concepts, including practical knowledge of Large Language Models (LLMs), NLP, computer vision, and predictive analytics. • Experience creating technical proposals, including user flows, technical architectures, and detailed solution documentation. • Excellent communication, presentation, and stakeholder management skills, with demonstrated ability to clearly articulate complex technical concepts to non-technical audiences. • Proven ability to manage multiple client engagements concurrently, coordinate with cross-functional teams, and deliver against tight deadlines. • Strong analytical skills, strategic thinking, and the ability to quickly adapt solutions to different industries, compliance frameworks, and business requirements. • Familiarity with AI tools and cloud platforms (Azure AI, AWS SageMaker, Google Cloud AI suite, etc.). Preferred Attributes: • Experience working with global clients, particularly in North America, Middle East, or Australia. • Self-motivated learner with a passion for emerging technologies and innovation. • Strong organizational skills and attention to detail, especially in preparing high-quality proposals and documentation

We are seeking a talented AI Engineer to join our team. The ideal candidate will have expertise in machine learning, NLP, deep learning, and deploying AI models, with experience in advanced tools and frameworks across AI and backend development. Responsibilities: Develop and deploy AI models using machine learning, deep learning (CNNs, RNNs, LSTMs), and NLP (GPT, BERT).Work with advanced AI frameworks (Langchain, AutoGen, Streamlit) and backend frameworks (FastAPI, Flask).Implement reinforcement learning and autonomous decision-making systems.Leverage cloud platforms (AWS: Bedrock, Sagemaker) for model deployment and scalability.Integrate third-party services (OpenAI, Azure Foundry) and tools (RelevanceAI, Huggingface).Work with databases (MongoDB, Postgres, Redis) and distributed systems.Utilize advanced AI techniques like RAG, fine-tuning, LoRA, QLoRA, multi-model systems, and stable diffusion.Explore AI applications in video generation models (text-to-video, image-to-video). Skills Needed: Expertise in AI frameworks: Langchain, AutoGen, Streamlit.Strong experience with FastAPI, Flask, and cloud platforms (AWS, Bedrock, Sagemaker).Knowledge of third-party services (OpenAI, Azure Foundry) and tools (RelevanceAI, Huggingface).Solid experience with databases (MongoDB, Postgres, Redis).Proficient in machine learning, deep learning, NLP, and reinforcement learning.Hands-on experience with advanced AI techniques: RAG, fine-tuning, LoRA, QLoRA, SLM, LLM, stable diffusion, and video generation models.

Job Title: Python Developer Experience: 2–4 Years Location: Onsite, Jodhpur, Rajesthan Type: Full-time No. of Openings: 4 Role Overview :We’re looking for a Python Developer with hands-on experience in ML model development, deployment, and integrating OpenAI APIs. You’ll work with cross-functional teams to build and scale intelligent applications . Key Responsibilitie s:Build and deploy ML models using Pytho n.Integrat e OpenAI AP Is (ChatGPT, Whisper, DALL·E, etc.) into application s.Deploy models vi a Dock er , FastA PI, an d cloud platfor ms (AWS/GCP/Azure ).Set up and maintai n CI/CD pipelin e s.Monitor and troubleshoot deployment and performance issue s. Must-Have Skil ls:Strong in Pyt ho n, Scikit-le ar n, Pan das, e tc.Experience wi th OpenAI API integrat i on.Familiarity wi th model deploym ent tools and workflo ws.Knowledge of CI /C D, Git, a nd RESTful A P Is.Solid problem-solving and debugging skil ls. Good to H ave:MLOps tools (MLflow, Kubef low)Cloud ML services (SageMaker, Vertex AI)

About Apexon: Apexon is a digital-first technology services firm specializing in accelerating business transformation and delivering human-centric digital experiences. We have been meeting customers wherever they are in the digital lifecycle and helping them outperform their competition through speed and innovation. Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the unlimited opportunities digital offers. Our reputation is built on a comprehensive suite of engineering services, a dedication to solving clients’ toughest technology problems, and a commitment to continuous improvement. Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon now has a global presence of 15 offices (and 10 delivery centers) across four continents. We enable #HumanFirstDigital Key Responsibilities: Design, develop, and maintain CI/CD pipelines for ML models and data workflows. Collaborate with data science teams to productionize models using tools like MLflow, Kubeflow, or SageMaker. Automate training, validation, testing, and deployment of machine learning models. Monitor model performance, drift, and retraining needs. Ensure version control of datasets, code, and model artifacts. Implement model governance, audit trails, and reproducibility. Optimize model serving infrastructure (REST APIs, batch/streaming inference). Integrate ML solutions with cloud services (AWS, Azure, GCP). Ensure security, compliance, and reliability of ML systems. Required Skills and Qualifications: Bachelor’s or master’s degree in computer science, Engineering, Data Science, or related field. 5+ years of experience in MLOps, DevOps, or ML engineering roles. Strong experience with ML pipeline tools (MLflow, Kubeflow, TFX, SageMaker Pipelines). Proficiency in containerization and orchestration tools (Docker, Kubernetes, Airflow). Strong Python coding skills and familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (AWS, Azure, GCP) and their ML services. Knowledge of CI/CD tools (GitLab CI/CD, Jenkins, GitHub Actions). Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, Sentry). Understanding of data versioning (DVC, LakeFS) and feature stores (Feast, Tecton). Strong grasp of model testing, validation, and monitoring in production environments. Our Commitment to Diversity & Inclusion: Did you know that Apexon has been Certified™ by Great Place To Work®, the global authority on workplace culture, in each of the three regions in which it operates: USA (for the fourth time in 2023), India (seven consecutive certifications as of 2023), and the UK.Apexon is committed to being an equal opportunity employer and promoting diversity in the workplace. We take affirmative action to ensure equal employment opportunity for all qualified individuals. Apexon strictly prohibits discrimination and harassment of any kind and provides equal employment opportunities to employees and applicants without regard to gender, race, color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. You can read about our Job Applicant Privacy policy here Job Applicant Privacy Policy (apexon.com) Our Perks and Benefits: Our benefits and rewards program has been thoughtfully designed to recognize your skills and contributions, elevate your learning/upskilling experience and provide care and support for you and your loved ones. As an Apexon Associate, you get continuous skill-based development, opportunities for career advancement, and access to comprehensive health and well-being benefits and assistance. We also offer: o Group Health Insurance covering family of 4 o Term Insurance and Accident Insurance o Paid Holidays & Earned Leaves o Paid Parental LeaveoLearning & Career Development o Employee Wellness

What You Need To Succeed Master’s degree or equivalent experience in Machine Learning. 3+ years of industry experience in ML, software engineering, and data engineering. Proficiency in Python, PyTorch, TensorFlow, and Scikit-learn. Strong programming skills in Python and JavaScript. Hands-on experience with ML Ops practices. Ability to work with research and product teams. Excellent problem-solving skills and a track record of innovation. Passion for learning and applying the latest technological advancements. Position Overview As a MLE-2, you will design, implement, and optimize AI solutions while ensuring model success. You will lead the ML lifecycle from development to deployment, collaborate with cross-functional teams, and enhance AI capabilities to drive innovation and impact. Key Responsibilities Design and implement AI product features. Maintain and optimize existing AI systems. Train, evaluate, deploy, and monitor ML models. Design ML pipelines for experiment, model, and feature management. Implement A/B testing and scalable model inferencing APIs. Optimize GPU architectures, parallel training, and fine-tune models for improved performance. Deploy LLM solutions tailored to specific use cases. Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks. Technical Requirements LLM & ML: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama LLMOps: MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI Databases: MongoDB, PostgreSQL, Pinecone, ChromDB Cloud: AWS, Azure DevOps: Kubernetes, Docker Languages: Python, SQL, JavaScript Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert What You'll Do Collaborate with cross-functional teams to design and build scalable ML solutions. Implement state-of-the-art ML techniques, including NLP, Generative AI, RAG, and Transformer architectures. Deploy and monitor ML models for high performance and reliability. Innovate through research, staying ahead of industry trends. Build scalable data pipelines following best practices. Present key insights and drive decision-making. Skills: scikit-learn,nlp,generative ai,kubernetes,python,ml ops,pytorch,data engineering,tensorflow,docker,aws,azure,machine learning,ml,javascript

:-Job Title: Machine Learning Engineer – 2 Location: Onsite – Bengaluru, Karnataka, India Experience Required: 3 – 6 Years Compensation: ₹20 – ₹25 LPA Employment Type: Full-Time Work Mode: Onsite Only (No Remote) About the Company:- A fast-growing Y Combinator-backed SaaS startup is revolutionizing underwriting in the insurance space through AI and Generative AI. Their platform empowers insurance carriers in the U.S. to make faster, more accurate decisions by automating key processes and enhancing risk assessment. As they expand their AI capabilities, they’re seeking a Machine Learning Engineer – 2 to build scalable ML solutions using NLP, Computer Vision, and LLM technologies. Role Overview:- As a Machine Learning Engineer – 2, you'll take ownership of designing, developing, and deploying ML systems that power critical features across the platform. You'll lead end-to-end ML workflows, working with cross-functional teams to deliver real-world AI solutions that directly impact business outcomes. Key Responsibilities:- Design and develop robust AI product features aligned with user and business needs Maintain and enhance existing ML/AI systems Build and manage ML pipelines for training, deployment, monitoring, and experimentation Deploy scalable inference APIs and conduct A/B testing Optimize GPU architectures and fine-tune transformer/LLM models Build and deploy LLM applications tailored to real-world use cases Implement DevOps/ML Ops best practices with tools like Docker and Kubernetes Tech Stack & Tools Machine Learning & LLMs GPT, LLaMA, Gemini, Claude, Hugging Face Transformers PyTorch, TensorFlow, Scikit-learn LLMOps & MLOps Langchain, LangGraph, LangFlow, Langfuse MLFlow, SageMaker, LlamaIndex, AWS Bedrock, Azure AI Cloud & Infrastructure AWS, Azure Kubernetes, Docker Databases MongoDB, PostgreSQL, Pinecone, ChromaDB Languages Python, SQL, JavaScript What You’ll Do Collaborate with product, research, and engineering teams to build scalable AI solutions Implement advanced NLP and Generative AI models (e.g., RAG, Transformers) Monitor and optimize model performance and deployment pipelines Build efficient, scalable data and feature pipelines Stay updated on industry trends and contribute to internal innovation Present key insights and ML solutions to technical and business stakeholders Requirements Must-Have:- 3–6 years of experience in Machine Learning and software/data engineering Master’s degree (or equivalent) in ML, AI, or related technical fields Strong hands-on experience with Python, PyTorch/TensorFlow, and Scikit-learn Familiarity with ML Ops, model deployment, and production pipelines Experience working with LLMs and modern NLP techniques Ability to work collaboratively in a fast-paced, product-driven environment Strong problem-solving and communication skills Bonus Certifications such as: AWS Machine Learning Specialty AWS Solution Architect – Professional Azure Solutions Architect Expert Why Apply Work directly with a high-caliber founding team Help shape the future of AI in the insurance space Gain ownership and visibility in a product-focused engineering role Opportunity to innovate with state-of-the-art AI/LLM tech Be part of a fast-moving team with real market traction 📍 Note: This is an onsite-only role based in Bengaluru. Remote work is not available. Skills: ml ops,software/data engineering,tensorflow,mongodb,llms,docker,machine learning,nlp,computer vision,python,azure,kubernetes,llms and modern nlp techniques,ml, ai,sql,llm technologies,python, pytorch/tensorflow, and scikit-learn,scikit-learn,postgresql,javascript,aws,pytorch

𝐉𝐨𝐛 𝐓𝐢𝐭𝐥𝐞: 𝐒𝐞𝐧𝐢𝐨𝐫 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐀𝐬𝐬𝐨𝐜𝐢𝐚𝐭𝐞 (𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧) – 𝐑𝐞𝐦𝐨𝐭𝐞 (𝐈𝐧𝐝𝐢𝐚) Location: Remote (Bengaluru, Hyderabad, Chennai) Engagement Type: Long-Term Contract Start Date: ASAP Work Hours: Overlap with EST time zone Dual Employment: Not permitted 𝐀𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐑𝐨𝐥𝐞: KheyDigit Global Solutions Pvt Ltd is seeking a Senior Machine Learning Associate with deep expertise in Computer Vision to support an international pharmaceutical manufacturing project. This role involves building, optimizing, and deploying AI/ML models that enable automated drug manufacturing line clearance using real-time camera feeds and anomaly detection via AWS infrastructure.You will be part of a global team and collaborate directly with international clients. This is a 100% remote opportunity with long-term growth potential. 𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: 1. Design, develop, and deploy computer vision models using AWS SageMaker. 2. Work on edge computing solutions using AWS Greengrass. 3. Support integration and optimization of models on Nvidia Triton GPU infrastructure. 4. Analyze HD camera feeds to detect anomalies in drug manufacturing line operations. 5. Build and train models to understand “normal” production line behavior and identify deviations. 6. Troubleshoot and enhance real-time AI/ML applications in a live production environment. 7. Collaborate with global technical and product teams; communicate fluently in English. 8. Remain adaptable and solution-oriented in a fast-paced, agile setup. 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐒𝐤𝐢𝐥𝐥𝐬 & 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: *5+ years of experience in Machine Learning, with a strong focus on Computer Vision. *Expert-level experience in AWS SageMaker and AWS Greengrass. *Experience in deploying models on GPU-based infrastructures such as Nvidia Triton. *Strong problem-solving skills with the ability to debug complex model and deployment issues *Excellent communication skills in English, able to work independently with international stakeholders. *Prior experience working in regulated or manufacturing environments is a plus. *Exposure to AI/ML use cases in Pharmaceutical or Manufacturing sectors. *Familiarity with model versioning, CI/CD pipelines, and MLOps practices. *Understanding of camera-based systems or computer vision libraries like OpenCV, PyTorch, or TensorFlow. 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐏𝐫𝐨𝐜𝐞𝐬𝐬: 15-minute HR Screening Technical Interview(s) with 1–2 client representatives

Location: Preferred: Ahmedabad, Gandhinagar, Hybrid (Can consider Remote case to case) Department: COE Experience: 8+ Years (with hands-on AI/ML architecture experience) Education: Ph.D. or Master's in Computer Science, Data Science, Artificial Intelligence, or related fields Job Summary: We are seeking an experienced AI/ML Architect with a strong academic background and industry experience to lead the design and implementation of AI/ML solutions across diverse industry domains. The ideal candidate will act as a trusted advisor to clients, understanding their business problems, and crafting scalable AI/ML strategies and solutions aligned to their vision. Key Responsibilities: Engage with enterprise customers and stakeholders to gather business requirements, problem statements, and aspirations. Translate business challenges into scalable and effective AI/ML-driven solutions and architectures. Develop AI/ML adoption strategies tailored to customer maturity, use cases, and ROI potential. Design end-to-end ML pipelines and architecture (data ingestion, processing, model training, deployment, and monitoring). Collaborate with data engineers, scientists, and business SMEs to build and operationalize AI/ML solutions. Present technical and strategic insights to both technical and non-technical audiences, including executives. Lead POCs, pilots, and full-scale implementations. Stay updated on the latest research, technologies, tools, and trends in AI/ML and integrate them into customer solutions. Contribute to proposal development, technical documentation, and pre-sales engagements. Required Qualifications: Ph.D. or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or related field. 8+ years of experience in the AI/ML field, with a strong background in solution architecture. Deep knowledge of machine learning algorithms, NLP, computer vision, deep learning frameworks (TensorFlow, PyTorch, etc.). Experience with cloud AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI, etc.). Strong communication and stakeholder management skills. Proven track record of working directly with clients to understand business needs and deliver AI solutions. Familiarity with MLOps practices and tools (Kubeflow, MLflow, Airflow, etc.). Preferred Skills: Experience in building GenAI or Agentic AI applications. Knowledge of data governance, ethics in AI, and explainable AI. Ability to lead cross-functional teams and mentor junior data scientists/engineers. Publications or contributions to AI/ML research communities (preferred but not mandatory).

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. Position: Associate Industry: CPG & Retail Domain: Range of Analytics (Descriptive to Advanced) depending on the client problem About Acceleration Center Bangalore At PwC, we connect people with diverse backgrounds and skill sets to solve important problems together and lead with purpose—for our clients, our communities and for the world at large. It is no surprise therefore that 429 of 500 Fortune global companies engage with PwC. Acceleration Centers (ACs) are PwC’s diverse, global talent hubs focused on enabling growth for the organization and value creation for our clients. The PwC Advisory Acceleration Center in Bangalore is part of our Advisory business in the US. The team is focused on developing a broader portfolio with solutions for Risk Consulting, Management Consulting, Technology Consulting, Strategy Consulting, Forensics as well as vertical specific solutions. PwC's high-performance culture is based on passion for excellence with a focus on diversity and inclusion. You will collaborate with and receive support from a network of people to achieve your goals. We will also provide you with global leadership development frameworks and the latest in digital technologies to learn and excel in your career. At the core of our firm's philosophy is a simple construct: We care for our people. Globally PwC is ranked the 3rd most attractive employer according to Universum. Our commitment to Responsible Business Leadership, Diversity & Inclusion, work-life flexibility, career coaching and learning & development makes our firm one of the best places to work, learn and excel. We are looking for experienced professionals with a strong data science background (and overall data science experience of 4+ years) to work in our Analytics Consulting practice in Mumbai and Bangalore. Senior Associate’s will work as an integral part of business analytics teams in India alongside clients and consultants in the U.S., leading teams for high-end analytics consulting engagements and providing business recommendations to project teams. Education: Advanced Degree in quantitative discipline such as Computer Science, Engineering, Econometrics, Statistics, Operations Research or Information Sciences such as business analytics or informatics. Required Skills: Successful candidates will have demonstrated the following skills and characteristics - Must-Have (Senior Associate - CPG & Retail Analytics) Hands-on experience with CPG & Retail data assets such as point-of-sale (POS) transactions, loyalty-program histories, syndicated panel data (NielsenIQ, Circana/IRI, Kantar), e-commerce clickstream, and supply-chain sensors/IoT. Deep understanding of predictive modeling for purchase propensity, demand forecasting, promotion uplift, assortment, and customer lifetime value in omnichannel retail environments. Proficiency in machine learning techniques—classification, regression, clustering, recommendation engines, and advanced time-series forecasting applied to sales and inventory data. Strong command of statistical methods including A/B & multivariate testing, price-elasticity modeling, market-basket analysis, segmentation, and causal-impact evaluation. Expert programming in Python or R, plus SQL with retail-specific data-wrangling libraries (pandas, dbt) across cloud warehouses (BigQuery, Redshift, Synapse). Hands on BI fluency in developing interactive visualizations in Power BI, Tableau, or Looker that turn SKU-level data into actionable stories for category, trade-marketing, and supply-chain teams. Exposure to big data & real-time analytics stacks used in retail (Spark, Kafka, Delta Lake, Snowflake Streaming, Google Vertex AI). Ability to translate insights for merchandising, marketing, supply-chain, and store-operations stakeholders—communicating clearly with both technical data teams and business leaders. Nice to have Exposure to ML engineering (Azure ML, AWS SageMaker, GCP Vertex AI) Experience blending retail-media impression/click logs with sales to calculate ROAS and incrementality, or to build MMM-lite dashboards for brand teams. Roles and Responsibilities Assist analytics projects within the CPG & Retail domain, driving design, development, and delivery of data science solutions Develop and execute on project & analysis plans under the guidance of Project Manager Interact with and advise consultants/clients in US as a subject matter expert to formalize data sources to be used, datasets to be acquired, data & use case clarifications that are needed to get a strong hold on data and the business problem to be solved Drive and Conduct analysis using advanced analytics tools and coach the junior team members Implement necessary quality control measures in place to ensure the deliverable integrity like data quality, model robustness, and explainability for deployments. Validate analysis outcomes, recommendations with all stakeholders including the client team Build storylines and make presentations to the client team and/or PwC project leadership team Contribute to the knowledge and firm building activities

At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions. In quality engineering at PwC, you will focus on implementing leading practice standards of quality in software development and testing processes. In this field, you will use your experience to identify and resolve defects, optimise performance, and enhance user experience. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills. As part of the AI Engineering team you will design, develop, and scale AI-driven web applications and platforms. As a Senior Associate you will analyze complex problems, mentor others, and maintain rigorous standards while building meaningful client connections and navigating increasingly complex situations. This role is well-suited for engineers eager to blend their entire stack development skills with the emerging world of AI and machine learning in a fast-paced, cross-functional environment. Responsibilities Design and implement AI-driven web applications and platforms Analyze complex challenges and develop impactful solutions Mentor junior team members and foster their professional growth Maintain exemplary standards of quality in every deliverable Build and nurture meaningful relationships with clients Navigate intricate situations and adapt to evolving requirements Collaborate in a fast-paced, cross-functional team environment Leverage broad stack development skills in AI and machine learning projects What You Must Have Bachelor's Degree in Computer Science, Software Engineering, or a related field 4-9 years of experience Oral and written proficiency in English required What Sets You Apart Bachelor's Degree in Computer Science, Engineering Skilled in modern frontend frameworks like React or Angular Demonstrating hands-on experience with GenAI applications Familiarity with LLM orchestration tools Understanding of Responsible AI practices Experience with DevOps tools like Terraform and Kubernetes Knowledge of MLOps capabilities Security experience with OpenID Connect and OAuth2 Experience in AI/ML R&D or cross-functional teams Preferred Knowledge/Skills Role Overview We are looking for a skilled and proactive Full Stack Engineer to join our AI Engineering team. You will play a pivotal role in designing, developing, and scaling AI-driven web applications and platforms. This role is ideal for engineers who are passionate about blending full stack development skills with the emerging world of AI and machine learning, and who thrive in cross-functional, fast-paced environments. Key Responsibilities Develop and maintain scalable web applications and APIs using Python (FastAPI, Flask, Django) and modern frontend frameworks (React.js, Angular.js). Build intuitive, responsive UIs using JavaScript/TypeScript, CSS3, Bootstrap, and Material UI for AI-powered products. Collaborate closely with product teams to deliver GenAI/RAG-based solutions. Design backend services for: Data pipelines (Azure Data Factory, Data Lake, Delta Lake) Model inference Embedding and metadata storage (SQL, NoSQL, Vector DBs) Optimize application performance for AI inference and data-intensive workloads. Integrate third-party APIs, model-hosting platforms (OpenAI, Azure ML, AWS SageMaker), and vector databases. Implement robust CI/CD pipelines using Azure DevOps, GitHub Actions, or Jenkins. Participate in architectural reviews and contribute to design best practices across the engineering organization. Required Skills & Experience 4–9 years of professional full-stack engineering experience. Bachelor's degree in Computer Science, Engineering, or related technical field (BE/BTech/MCA) Strong Python development skills, particularly with FastAPI, Flask, or Django. Experience with data processing using Pandas. Proficient in JavaScript/TypeScript with at least one modern frontend framework (React, Angular). Solid understanding of RESTful and GraphQL API design. Experience with at least one cloud platform: Azure: Functions, App Service, AI Search, Service Bus, AI Foundry AWS: Lambda, S3, SageMaker, EC2 Hands-on experience building GenAI applications using RAG and agent frameworks. Database proficiency with: Relational databases: PostgreSQL, SQL Server NoSQL databases: MongoDB, DynamoDB Vector stores for embedding retrieval Familiarity with LLM orchestration tools: LangChain, AutoGen, LangGraph, Crew AI, A2A, MCP Understanding of Responsible AI practices and working knowledge of LLM providers (OpenAI, Anthropic, Google PaLM, AWS Bedrock) Good To Have Skills DevOps & Infrastructure: Terraform, Kubernetes, Docker, Jenkins MLOps capabilities: model versioning, inference monitoring, automated retraining Security experience with OpenID Connect, OAuth2, JWT Deep experience with data platforms: Databricks, Microsoft Fabric Prior experience in AI/ML R&D or working within cross-functional product teams

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills. As part of the Data Science team you will design and deliver scalable AI applications that drive business transformation. As a Senior Associate you will analyze complex problems, mentor junior team members, and build meaningful client connections while navigating the evolving landscape of AI and machine learning. This role offers the chance to work on innovative technologies, collaborate with cross-functional teams, and contribute to creative solutions that shape the future of the industry. Responsibilities Design and implement scalable AI applications to facilitate business transformation Analyze intricate problems and propose practical solutions Mentor junior team members to enhance their skills and knowledge Establish and nurture meaningful relationships with clients Navigate the dynamic landscape of AI and machine learning Collaborate with cross-functional teams to drive innovative solutions Utilize advanced technologies to improve project outcomes Contribute to the overall strategy of the Data Science team What You Must Have Bachelor's Degree in Computer Science, Engineering, or equivalent technical discipline 4-9 years of experience in Data Science/ML/AI roles Oral and written proficiency in English required What Sets You Apart Proficiency in Python and data science libraries Hands-on experience with Generative AI and prompt engineering Familiarity with cloud platforms like Azure, AWS, GCP Understanding of production-level AI systems and CI/CD Experience with Docker, Kubernetes for ML workloads Knowledge of MLOps tooling and pipelines Demonstrated track record of delivering AI-driven solutions Preferred Knowledge/Skills Please reference About PwC CTIO – AI Engineering PwC’s Commercial Technology and Innovation Office (CTIO) is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The AI Engineering team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next—enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence.ill categories for job description details. Role Overview We are seeking a Senior Associate – Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 9 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI, including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems.

Location : Mumbai / Pune (Work from Office, with flexibility on need basis) Employment Type : Full-Time Experience : 4-8 Years Reports To : Director - Machine Learning and Gen AI About The Role We are looking for a hands-on and solution-oriented Senior Data Scientist - Generative AI to join our growing AI practice. This role is ideal for someone who thrives in designing and deploying Gen AI solutions on AWS, enjoys working with customers directly, and can lead end-to-end implementations. You will play a key role in architecting AI solutions, driving project delivery, and guiding junior team members. Key Responsibilities artif- Design and implement end-to-end Generative AI solutions for customers on AWS. Work closely with customers to understand business challenges and translate them into Gen AI use-cases. Own technical delivery, including data preparation, model integration, prompt engineering, deployment, and performance monitoring. Lead project execution - ensure timelines, manage stakeholder communications, and collaborate across internal teams. Provide technical guidance and mentorship to junior data scientists and engineers. Develop reusable components and reference architectures to accelerate delivery. Stay updated with latest developments in Gen AI, particularly AWS offerings like Bedrock, SageMaker, LangChain integrations, etc. Required Skills & Experience 4 to 8 years of hands-on experience in Data Science/AI/ML, with at least 2 years in Generative AI projects. Proficient in building solutions using AWS AI/ML services (e.g., SageMaker, Amazon Bedrock, Lambda, API Gateway, S3, etc.). Experience with LLMs, prompt engineering, RAG pipelines, and deployment best practices. Solid programming experience in Python, with exposure to libraries such as Hugging Face, LangChain, etc. Strong problem-solving skills and the ability to work independently in customer-facing roles. Experience in collaborating with Systems Integrators (SIs) or working with startups in India is a major plus. Soft Skills Strong verbal and written communication for effective customer engagement. Ability to lead discussions, manage project milestones, and coordinate across stakeholders. Team-oriented with a proactive attitude and strong ownership mindset. What We Offer Opportunity to work on cutting-edge Generative AI projects across industries. Collaborative, startup-like work environment with flexibility and ownership. Exposure to full-stack AI/ML project lifecycle and client-facing roles. Competitive compensation and learning opportunities in the AWS AI ecosystem. About Oneture Technologies Founded in 2016, Oneture is a cloud-first, full-service digital solutions company, helping clients harness the power of Digital Technologies and Data to drive transformations and turning ideas into business realities. Our team is full of curious, full-stack, innovative thought leaders who are dedicated to providing outstanding customer experiences and building authentic relationships. We are compelled by our core values to drive transformational results from Ideas to Reality for clients across all company sizes, geographies, and industries. Oneture team delivers full lifecycle solutions-from ideation, project inception, planning through deployment to ongoing support and maintenance. Our core competencies and technical expertise includes Cloud powered : Product Engineering, Big Data and AI ML. Our deep commitment to value creation for our clients and partners and "Startups-like agility with Enterprises-like maturity" philosophy has helped us establish long-term relationships with our clients and enabled us to build and manage mission-critical platforms for them. (ref:hirist.tech)

Hiring data engineers for glbal consulting firm in Gurgaon, Pune, Noida location. Experience - 4-10 years Core Skills ∙Data Architecture & SQL Engineering: Advanced SQL, data modeling (3NF, star, snowflake), dimensional design ∙Cloud Warehousing Expertise: Familiarity with Snowflake ∙Power BI Data Modeling: Dataflows, composite models, import vs. direct query trade- offs ∙Scalability: Partitioning strategies, incremental refresh policies, usage of materialized views ∙ETL Design: Tools such as Jenkins and SageMaker ∙Monitoring & Observability: Usage of Power BI Performance Analyzer, DAX Studio, Azure Monitor Tasks / Projects ∙Conduct audits on existing tables, dataflows, and report dependencies ∙Evaluate and optimize data model architecture to ensure refresh efficiency and query speed ∙Implement Power BI best practices: minimized cardinality, star schemas, avoidance of bidirectional filters ∙Develop documentation and governance policies for long-term sustainability ∙Define a scalable data layer and architecture principles ∙Coordinate with infrastructure teams on capacity planning and workload management ∙Future - Prototype new architectures that incorporate AI summarization (LLM integration)