Senior ML Engineer / Applied Scientist – RAG, Agentic Systems, vLLM / SG Lang & Vector Databases (Prod
We’re building next-gen AI-powered product experiences — intelligent assistants, agentic workflows, and scalable RAG systems. We’re hiring a Senior ML Engineer / Applied Scientist who can build production-grade RAG architectures , develop agentic systems (LangGraph, CrewAI, AutoGen), and deploy high-performance LLM inference using vLLM, SGLang, TensorRT-LLM , while working with modern vector databases (Qdrant, MongoDB Vector Search) .
This is a hands-on role at the intersection of AI systems, retrieval, agents, and product engineering.
What You’ll Do
Build end-to-end RAG pipelines (ingestion → embeddings → vector DB → retrieval → generation).
Work with open-source models (LLaMA, Mistral, Qwen, Gemma) and closed-source models (GPT-4.x, Claude 3, Gemini, Grok).
Develop agentic workflows using LangGraph, CrewAI, AutoGen, LangChain, LlamaIndex .
Deploy & optimize inference using vLLM, SGLang, TensorRT-LLM, TGI .
Implement scalable vector search with Qdrant & MongoDB Atlas Vector Search .
Build multilingual pipelines with Indic-language support.
Set up evaluation using Ragas, DeepEval, LangSmith, TruLens .
Work closely with backend / product teams to deploy RAG + agent systems in production.
What You Bring
4–8+ years in ML engineering, NLP, or LLM-based product development.
Strong hands-on RAG experience (chunking, embeddings, reranking, retrieval optimization).
Experience with Qdrant , MongoDB Vector Search , FAISS, Milvus, Pinecone, or Weaviate.
Practical experience with vLLM , SGLang , model routing, and inference optimization.
Proficiency with LangGraph , CrewAI , AutoGen , LangChain , or LlamaIndex .
Experience integrating both open-source and closed-source LLMs.
Ability to ship production systems with strong reliability, latency, and quality.
Bonus Skills
Knowledge graphs, semantic retrieval, long-context models.
Multi-agent systems & complex tool-routing workflows.
Experience with Indic languages and OCR pipelines.
Join us to build the AI backbone of next-generation product experiences.
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