Machine Learning Engineer - Large Language Models

Stack

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Descrizione

We are seeking a highly skilled and experienced Machine Learning Engineer to join our team. The ideal candidate will have a robust background in machine learning, natural language processing (NLP), and Large Language Models (LLMs). The role focuses on training, tuning, and evaluating AI models as part of a diverse team which includes professionals from software engineering, data science, and medicine. Key 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. Requirements: • 5+ years of hands-on professional experience in software engineering, building production-grade deep learning solutions. • An academic degree in computer science, data science, or a related degree. M.Sc. or Ph.D. degree is strongly preferred. • Demonstrated expertise in model tuning frameworks like Axolotl. • Familiarity with model serving frameworks, including vLLM, TGI, and llama-cpp, to support the deployment and scalability of machine learning models. • Knowledge of

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