Machine Learning Engineer - Large Language Models

Responsibilities

• Adapt LLMs to diverse healthcare use-cases using techniques such as Sparse Fine-Tuning (SFT), Prompt Engineering Fine-Tuning (PEFT), Direct Parameter Optimization (DPO), and Proximal Policy Optimization (PPO).
• Optimize LLMs for Retriever-Augmented Generation (RAG) to enhance decision-making and information retrieval capabilities.
• Collect, clean, and refine healthcare datasets for training LLMs to ensure high-quality data provisioning.
• Convert models into various formats suitable for production environments, ensuring their readiness for real-world application.

Languages