Machine Learning Engineer (Contract)

About this ML Engineer role at Centre for Development of Advanced Computing (C-DAC) Pune

You'll join C-DAC Pune as a contract ML Engineer supporting India's National Supercomputing Mission and IndiaAI compute infrastructure. This is a direct-apply government-research role in Pune that lets you work on large-scale AI optimization for Indian supercomputing facilities—a rare opportunity to shape the nation's AI infrastructure while building deep expertise in distributed training at scale.

What you'll do

• Optimize large language model (LLM) training pipelines to run efficiently on India's supercomputing infrastructure
• Write and refine Python code using distributed training frameworks like Horovod and DeepSpeed to accelerate model training
• Benchmark and measure performance improvements using CUDA and deep learning optimization techniques
• Support academic researchers who are using AI compute grants on C-DAC's platforms
• Collaborate on projects under the National Supercomputing Mission to push India's AI capability forward

Who should apply

You'll need a B.Tech or M.Tech in Computer Science, IT, AI, or ECE with 2–5 years of industry experience—so mid-level ML Engineers and senior junior engineers with proven depth in deep learning. This is not a fresher role; you should have shipped production models or optimized real training workflows. Strong Python skills and at least basic familiarity with CUDA are expected.

Salary & offer in context

C-DAC offers ₹60,000–₹85,000 per month for this contract position. For a mid-level ML Engineer salary in India, this sits solidly in the competitive mid-market range; research roles at government institutions often trade slightly below top-tier private AI labs for the prestige, learning opportunity, and job security of a 1-year renewable contract.

Path to apply

This is a direct-apply role with no entrance exam required—you apply online through C-DAC's portal, then proceed to a written test for shortlisting followed by an interview. The deadline is May 28, 2026, so apply soon if this aligns with your goals. This is a 1-year contract, renewable, giving you a structured way to deepen your expertise in distributed training and LLM optimization.