ML / Fine-Tuning Engineer

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.

Benefits

• Comprehensive Medical Coverage:
  Health insurance
  of INR 5.0 Lakhs for you and your family (up to 6
  members), ensuring complete peace of mind.
• Robust Protection Plans:
  Group Personal Accident
  Insurance and Group Term Life Insurance to safeguard you and
  your loved ones.
• Retirement Benefits:
  PF and Gratuity provided as
  per standard government regulations.
• Flexible Work Options:
  Enjoy hybrid work
  arrangements & flexible working hours.
• Generous Leave Policy:
  21 days of annual leave, in
  addition to 10 company-declared holidays.
• Employee Well-being Spaces:
  Access to a dedicated
  break-out area with round-the-clock refreshments for
  relaxation and rejuvenation.