Primary Skills: Agentic AI, Pytorch, RAG, ML, Gen AI Description: Key Responsibilities - Build and deploy scalable LLM, RAG, and agent-based systems - Architect LLM inference and deployment pipelines - Optimize models for efficient and cost-effective production - Collaborate with data science, research, and product teams - Ensure clean code, testing, reproducibility, and CI/CD - Mentor junior engineers and drive engineering best practices - Ensure ethical, secure, and responsible AI development Required Skills - Advanced Python with strong fundamentals in NumPy, Pandas, scikit-learn - Deep learning expertise in PyTorch / TensorFlow - Hands-on with LLM frameworks: Hugging Face Transformers, LangChain (prompting fine-tuning) - Solid experience with Agentic AI frameworks: AutoGen, CrewAI, LangGraph - Expertise in RAG pipelines, semantic search, vector databases - Strong software engineering practices: microservices, TDD,



concurrency - Ability to rapidly prototype and productionize GenAI solutions Good-to-Have Skills - Model optimization: Quantization (GPTQ, AWQ), pruning, distillation - Multimodal AI (text, vision, audio): CLIP, BLIP, Whisper, LLaVA - LLM serving using FastAPI and vector DBs (FAISS, Pinecone, Chroma) - CI/CD pipelines, Airflow, Docker, Kubernetes / Helm - Cloud AI deployments on AWS / Azure / GCP (e.g., SageMaker) - MLOps tracking: Git, MLflow - Data pipelines ELT/ETL using Snowflake

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📌 Lead I - ML Engineering(AI,ML,Python) (Bengaluru)
🏢 UST
📍 Bengaluru