Description

Own the end-to-end development, fine-tuning, and optimization of LLMs and deep learning models for production healthcare environments.

Develop training pipelines, manage datasets, and execute automated tests to validate AI outputs. Write high-quality prompts and training examples to shape model behavior. Design and maintain instruction orchestration and evaluation workflows. Analyze model performance, identify failure patterns such as hallucinations, and drive improvements. Optimize LLM workloads on AWS, focusing on GPU utilization and cost-efficient inference.

Responsibilities

• Develop, fine-tune, and optimize LLMs (GPT, LLaMA, Mistral) for production use.
• Design and maintain instruction orchestration and evaluation workflows.
• Build training pipelines and manage datasets for model training.
• Execute automated tests and regression testing to validate AI output quality.
• Analyze model performance and drive improvements on reliability and consistency.

Required Skills

• 7+ years of experience in machine learning, NLP, or deep learning.
• Strong Python skills with experience in PyTorch or TensorFlow.
• Hands-on experience with LLMs in applied or production contexts.
• Required healthcare data experience, including working knowledge of healthcare datasets.
• Familiarity with HuggingFace tools and modern model-training workflows.
• Experience optimizing LLM workloads on AWS, including GPU utilization.
• Experience designing automated evaluation, regression testing, or benchmarking pipelines.

Preferred Skills

• Ability to work with minimal direction and take ownership in ambiguous problem spaces.
• Excellent communication skills for technical documentation and evaluation artifacts.

Key Skills

Education

Any Gradute