Job Description
Key Responsibilities:
- Design and implement Generative AI applications using LLMs, RAG (Retrieval-Augmented Generation), and Agentic AI frameworks.
- Develop and fine-tune LLMs leveraging frameworks such as LangChain, Hugging Face Transformers, and LangGraph.
- Build prompt engineering pipelines and ensure optimal model performance for specific business use cases.
- Implement MLOps practices for model versioning, training automation, and continuous integration using MLflow, AWS SageMaker, or Azure ML.
- Architect and optimize vector database integrations (e.g., FAISS, Pinecone, Chroma, Weaviate).
- Work closely with data engineers and product teams to operationalize AI workflows.
- Deploy, monitor, and optimize AI/ML models in production on AWS / Azure environments.
- Ensure AI governance, security, and ethical compliance across all AI deployments.
- Collaborate with cross-functional teams to evaluate new too...
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