ML Ops Engineer, Chanakya

• 3–5 years in ML engineering or MLOps with at least one production LLM or ML system in continuous operation

• Deep expertise in model serving: vLLM, TGI, Triton Inference Server, or equivalent; experience with quantised model formats (GGUF, AWQ, GPTQ)

• Experience fine-tuning and adapting models in constrained, on-prem, or air-gapped environments, including managing data pipelines and compute limitations specific to the environment

• Containerisation experience with Docker, Kubernetes, or lightweight alternatives (K3s, K0s) for constrained and edge environments; familiarity with deploying across heterogeneous hardware and infrastructure configurations

• Monitoring and observability using Prometheus, Grafana, or equivalent; ability to build custom eval dashboards

• Python fluency; familiarity with fine-tuning workflows and model evaluation frameworks

• Hands-on experience with CI/CD tooling for ML pipelines: GitHub Actions, ArgoCD, DVC, or similar

• You've kept a production ML system running under load — and debugged it when it broke

• You don't wait for things to fail; you build systems that tell you when they're about to

• You write documentation that actually gets used, by people who aren't you

• You treat uptime and correctness as equally non-negotiable

• You understand that operational reliability is a form of trust-building

• You're as comfortable optimising inference throughput as you are writing a field runbook for a deployment engineer

• You take ownership of model and stack health across every active deployment — not just the ones you set up

Sarvam is a fast-moving, high talent-density team building full-stack AI for India, working on problems that push the frontiers of AI with real population-scale impact.

• Work alongside researchers, engineers, builders, and business leaders who move fast and hold each other to a very high bar

• High ownership and high impact, from day one

• Everything we do is AI-first, from the way we build and ship to the way we think about problems

• You can work on problems that could change how an entire country learns, works, and communicates

If you want to work on problems at the frontier of AI in India, Sarvam is the place to be.