About the Role
Base model selection and fine-tuning quality are the foundation everything else is built on — the default recipes here shape how well every downstream model performs. As a Fine-Tuning Research Scientist, you'll own that foundation.

What You'll Do
• Select and evaluate base models for fine-tuning suitability
• Design and maintain instruction-tuning and supervised fine-tuning recipes, including LoRA/QLoRA adapters
• Support customer-specific tuning requests as reference implementations for the wider platform
• Run and interpret fine-tuning ablations to keep our default recipes current with the field
• Collaborate with our evaluation team to validate fine-tuning quality against real benchmarks What You'll Bring




• 5+ years of relevant experience in applied machine learning or NLP
• Robust hands-on experience fine-tuning large language models, including LoRA/QLoRA
• Proficiency with PyTorch and the Hugging Face ecosystem
• Comfort running and interpreting training ablations at scale
• Solid grounding in evaluation methodology, to know whether a fine-tune actually improved the model Education Master's or PhD in Machine Learning, Computer Science, Statistics, or a related quantitative field. Nice to Have
• A master's or PhD in Machine Learning or NLP
• Experience fine-tuning models at an applied AI company

📌 Fine-Tuning Research Scientist (Bengaluru)
🏢 HCLTech
📍 Bengaluru