Live opening · Posted 18 days ago
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About the role
Description supplied by the original job listing.
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.
Experience
4-8 yrs
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