ML / Fine-Tuning Engineer

Job Summary

Job Title: ML / Fine-Tuning Engineer

Location: Hyderabad OR Pune

Notice Period: 0-30 Days

Mode of Work: Hybrid

Experience: 5+ Years

We are looking for ML / Fine-Tuning Engineer who can deliver (under supervision of ProServe Tech Lead) the end-to-end fine-tuning of open-source LLMs for a narrow, high-volume production task on AWS SFT and alignment experiments (GRPO, DPO), debugging training on multi-GPU clusters, and iterating to strict accuracy targets. Models from 8B to 70B parameters.

What We Expect

• Fine-tune open-source LLMs (Qwen, Llama) from experiment to production-ready checkpoint
• Run SFT and RL alignment (GRPO, DPO) to improve output accuracy
• Execute training on AWS GPU instances (p4d, p5, g5) using distributed training
• Diagnose/fix training issues: loss imbalances, OOM errors, gradient instabilities
• Collaborate with evaluation and data engineering to iterate on quality gaps
• Make data-driven model scaling decisions (8B 14B 70B) based on offline metrics

Requirements

• Experience: 5+ years ML engineering, with 2+ years in LLM fine-tuning
• LLM Models: Hands-on with open-source LLMs Qwen and Llama required
• Training Methods: SFT, LoRA/QLoRA, GRPO, DPO/RLHF
• Frameworks: NVIDIA NeMo/NeMoRL, VeRL, HuggingFace TRL must have used at least two
• Distributed Training: DeepSpeed ZeRO, FSDP2, multi-node GPU orchestration
• AWS Infrastructure: p4d/p5/g5 GPU instances, SageMaker Training Jobs
• Languages: Python, PyTorch; CUDA debugging a plus

Preferred (Not Required)

Fine-tuning for tool-calling/agent tasks; multi-node GRPO/RLHF with NeMoRL or VeRL; tokenizer internals and chat-template rendering for tool-use formats.

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