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LLM Engineer

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LLM Engineers build, fine-tune, evaluate, and deploy large language model systems in production — from running LoRA/QLoRA adapter training on Llama 3 and Mistral variants, to standing up vLLM or TGI inference endpoints, to architecting multi-stage RAG pipelines that ground model outputs in proprietary data. In India through 2026, the role is dominated by demand from Sarvam AI, Krutrim, Karya.ai, Fractal Analytics, Mu Sigma, and the FAANG-India AI teams (Google DeepMind India, Microsoft AI, Amazon AWS India), plus a growing pipeline of US-remote opportunities at Anthropic, Together AI, and OpenAI that pay dollar salaries to engineers in Bengaluru and Hyderabad. The role demands a rare triple: deep ML understanding (attention mechanisms, tokenization, training dynamics), software-engineering discipline (async inference APIs, eval harnesses, prompt version control), and production reliability instincts (GPU cost optimization, latency budgets, observability for non-deterministic systems).