Tata Consultancy Services
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AI ML Engineer
role at
Tata Consultancy Services .
Overview We are looking for a highly skilled and passionate AI/ML Engineer to join our AI/ML team.
Responsibilities
Work with data scientists/data engineers to translate prototypes and theoretical models into functional, production-ready code.
Collaborate with product, engineering, and research teams to integrate AI/ML into applications and services.
Research, evaluate, and implement the latest advancements in AI/ML and large language models (LLMs).
Productionalize the AI/ML model in Hadoop environment.
Work with vector databases (e.g., FAISS, PGVector, Pinecone) for retrieval-augmented generation (RAG) and semantic search use cases.
Design scalable, observable, and resilient AI/ML models for real-world applications.
Monitor model performance and continuously improve efficiency, accuracy, and user experience.
Qualifications
Strong experience in deep learning and NLP, especially LLMs and generative models.
Proficiency in Python and ML libraries such as Hugging Face Transformers, LangChain, and OpenAI APIs.
Experience with prompt engineering, few-shot learning, and fine-tuning LLMs.
Familiarity with ML Ops/LLMOps and distributed systems.
Experience working with vector databases and RAG pipelines.
Solid understanding of system design patterns, scalability, observability, and performance tuning.
Strong analytical and problem-solving skills.
Passion for exploring and building with emerging AI technologies.
Bachelor of Computer Science.
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AI ML Engineer
role at
Tata Consultancy Services .
Overview We are looking for a highly skilled and passionate AI/ML Engineer to join our AI/ML team.
Responsibilities
Work with data scientists/data engineers to translate prototypes and theoretical models into functional, production-ready code.
Collaborate with product, engineering, and research teams to integrate AI/ML into applications and services.
Research, evaluate, and implement the latest advancements in AI/ML and large language models (LLMs).
Productionalize the AI/ML model in Hadoop environment.
Work with vector databases (e.g., FAISS, PGVector, Pinecone) for retrieval-augmented generation (RAG) and semantic search use cases.
Design scalable, observable, and resilient AI/ML models for real-world applications.
Monitor model performance and continuously improve efficiency, accuracy, and user experience.
Qualifications
Strong experience in deep learning and NLP, especially LLMs and generative models.
Proficiency in Python and ML libraries such as Hugging Face Transformers, LangChain, and OpenAI APIs.
Experience with prompt engineering, few-shot learning, and fine-tuning LLMs.
Familiarity with ML Ops/LLMOps and distributed systems.
Experience working with vector databases and RAG pipelines.
Solid understanding of system design patterns, scalability, observability, and performance tuning.
Strong analytical and problem-solving skills.
Passion for exploring and building with emerging AI technologies.
Bachelor of Computer Science.
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