About the role
Responsibilities:
- Fine-tuning pipelines using LoRA / QLoRA / PEFT on domain-specific corpora.
- Synthetic training data generation (JSONL) for healthcare NLP tasks.
- Model evaluation design: precision, recall, and task-specific rubrics for clinical and billing language.
- Quantisation and inference optimisation (GGUF, AWQ, bitsandbytes) for GPU-constrained deployments.
- Prompt engineering as a systematic, reproducible discipline.
- Benchmarking SLMs against frontier models on narrow, well-defined tasks.
Requirements:
- Background that maps well: NLP research, LLM fine-tuning at a product company, applied AI in healthtech or regulated domains, M. Tech / PhD with hands-on model training experience.