Senior Machine Learning Engineer
Build and deploy LLM-powered agents and production AI/NLP pipelines, focusing on RAG, agentic systems, model optimization, and scalable deployment. The role requires 3+ years of machine learning or applied AI experience, strong Python skills, and experience with modern ML frameworks and infrastructure.
About the job
Responsibilities
- Build and deploy LLM-powered agents for internal tools and customer-facing products.
- Design and improve RAG pipelines, prompt engineering workflows, and tool integrations.
- Experiment with open-source and closed-source LLMs.
- Implement and evaluate reasoning, planning, memory, and retrieval modules for AI agents.
- Optimize ML and LLM systems for accuracy, latency, scalability, and cost.
- Build production-ready AI/NLP pipelines with monitoring, evaluation benchmarks, and continual improvement loops.
- Collaborate with product, engineering, and customer-facing teams to ship impactful AI features.
Requirements
- B.Tech, M.Tech, or PhD in computer science or a mathematics-related field from a tier-1 engineering institute.
- 3+ years of industry experience in machine learning and NLP, or applied AI.
- Strong programming skills in Python.
- Interest and experience with RAG and agentic AI concepts.
- Experience with PyTorch, Hugging Face Transformers, and similar ML libraries.
- Interest and experience in model training, inference optimization, and GPUs.
- Experience deploying ML services using REST APIs, Docker, Kubernetes, or cloud platforms.
- Exposure to vector databases such as FAISS, Pinecone, Qdrant, or similar.
Skills
Python, LLMs, Retrieval-Augmented Generation, Prompt Engineering, Agentic AI, PyTorch, Hugging Face Transformers, NLP, Gpu Computing, REST APIs, Docker, Kubernetes, Faiss, Pinecone, Qdrant
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