Pioneers innovative ML techniques and builds foundation models for clinical information extraction and synthesis from medical records. Requires PhD in CS/math with NLP/ML focus, high-impact publications, and experience with large-scale model training using PyTorch/JAX.
200k – 250k/yr
On-siteAI Research
About the role
Responsibilities
Design and implement state-of-the-art machine learning techniques to advance Layer Health's research agenda (in areas such as information extraction, multimodal reasoning, and summarization).
Propose new agentic methods that tackle fundamental NLP and ML challenges such as modeling over multiple documents, long contexts, multiple modalities, and with limited or noisy labels.
Build foundation models to power the future of clinical information extraction & synthesis, from training through inference.
Stay up-to-date and actively engage with cutting-edge research in NLP, generative AI, and clinical machine learning.
Collaborate with the broader engineering team to ship performant products that meet user needs.
Cultivate and foster a robust and thoughtful R&D culture that drives the company forward.
Requirements
Exceptional methodological research background and experience, including a PhD in computer science/applied mathematics or equivalent research experience, specializing in natural language processing and machine learning.
High-impact, early-author publications at top peer-reviewed ML journals/conferences.
Demonstrated record of delivering real-world impact from start to finish – with the ability to design, develop, and ship innovations.
Strong programming skills and fluency with modern machine learning/LLM stacks (PyTorch, Jax).
Past experience in training/inference of foundation models (billions of parameters, distributed training, familiarity with state-of-the-art techniques).
A strong communicator who thrives in a customer-focused, fast-paced environment.
An excited and adaptable team player who wants to disrupt the healthcare industry with AI/ML.
Nice-to-Haves
Past experience in healthcare or life sciences.
Compensation
Expected compensation range: $200,000-250,000, in addition to stock options. Compensation dependent on experience, fit, and location.
Skills
PyTorchJAXNatural Language ProcessingMachine LearningLLMsFoundation ModelsDistributed TrainingInformation ExtractionMultimodal ReasoningGenerative AI
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