ML Postdoc Researcher - LLMs & Generative AI

Truveta
Seattle, WAPosted 26 March 2026

Job Description

ML Postdoc Researcher - LLMs Generative AI Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture. Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote Who We Need We are seeking a highly motivated and talented Machine Learning Postdoctoral Researcher to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. Program Details Our Postdoctoral Research program is designed for candidates who have completed their PhD within the last two years and worked in their area of expertise since graduation as a postdoc, professor, or industry researcher/scientist. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our postdoc research programs are designed to be a minimum of 3 months and a maximum of 12 months, with the opportunity to extend beyond the initially agreed term based on the company’s needs and the candidate’s desires. This Opportunity We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better. In this role, you will: Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications. Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks. Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy. Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning. Deliver the next generation of innovation in trustworthy healthcare. Key Qualifications Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI Strong theoretical and practical background in NLP including experience with state-of-the-art architectures Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI Solid programming skills in Python and the ability to write clean, efficient, and well-documented code Excellent probl ... (truncated, view full listing at source)
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