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Hybrid Bengaluru senior ML role with mid-level experience but niche LLM requirements limits mass applicant density.
Requires specialized LLM/ML frameworks, vector search and production inference expertise, limiting cross-industry transferability.
Explicit 5+ years, 2+ LLM years and many mandatory LLM, infra, and tooling requirements.
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Architect and lead design of complex AI systems including multi-agent orchestration, large-scale Retrieval-Augmented Generation (RAG) pipelines, and production Large Language Model (LLM) infrastructure.
Own end-to-end delivery of critical AI features from conception to production including design documentation, implementation, and rollout strategy.
Drive technical direction for AI platform components, establish frameworks and best practices, mentor junior engineers, and optimize systems for performance, cost, and reliability.
Minimum 5+ years software engineering experience with at least 2+ years building production LLM/Generative AI systems at scale.
Expert-level Python skills including async programming, performance optimization, and production-grade testing.
Strong system design skills with hands-on experience in ML/LLM frameworks (PyTorch, Hugging Face, LangChain, LlamaIndex, or Ray) and vector search systems (Elasticsearch, Pinecone, Weaviate, FAISS).
Located in India and able to work hybrid with occasional onsite presence in Bengaluru office.
Experienced in building and scaling AI-driven enterprise-grade cloud applications with a focus on production reliability and cost optimization.
Proven technical leadership capabilities in driving architecture decisions, mentoring engineers, and collaborating cross-functionally with product and data science teams.
Deep expertise in LLM optimization techniques including prompt engineering, fine-tuning, embeddings, and inference optimization aligned with AI platform development.