Machine Learning Scientist

Summary

Join Natera's Artificial Intelligence and Machine Learning team as a Machine Learning Scientist to contribute to cutting-edge research and development in molecular therapeutics and biomarker discovery. Implement and expand state-of-the-art deep learning models and foundation models in biomedicine. Leverage hands-on experience and a proven track record to interpret model results and revolutionize medical diagnostics and therapeutics. Collaborate with researchers and medical professionals. Design, implement, and evaluate biomedical foundation models and large language models (LLMs). Stay current with advancements in AI/ML and biomedical literature, applying cutting-edge approaches to solve complex problems.

Requirements

• PhD in Computer Science, Statistics, Bioinformatics, or a related quantitative field; or Master’s in the above fields with 3+ years of experience
• Proven experience with biomedical and molecular foundation models, graph neural networks, modality fusion, representation learning, generative models, and self-supervised learning techniques; and a demonstrated track record of machine learning applications to genomics multi-omics data and therapeutics discovery
• Highly proficient in PyTorch, Huggingface APIs, tensorboard, captum, scikit-learn, transformers
• Experience with SQL databases (snowflake and mysql-server)
• Experience in Git, jupyter notebook, and advanced visualizations (seaborn, plotly)
• Experience with AWS, and multiple GPU-accelerated environments
• Ability to clearly summarize and communicate results in oral and written form
• High scientific rigor and eagerness to teach and learn about new machine learning methods and biology

Responsibilities

• Design, implement, and evaluate biomedical foundation models and large language models (LLMs), with scientific rigor for applications focused on therapeutics and prognostics
• Independently explore and stay current with the latest advancements in AI/ML and biomedical literature, applying cutting-edge AI/ML approaches to solve complex problems in molecular therapeutics
• Interpret machine learning models by explainable AI methods (e.g. GradCAM, Shap) on diverse data modalities, such as genomics, transcriptomics and imaging, generating insights to enhance model transparency and trust
• Document code and model by maintaining well-structured, readable, and reproducible workflows. Use version control systems (e.g. Git) and reproducible demos (e.g. Jupyter notebooks) to ensure consistency across projects
• Communicate scientific results effectively through internal meetings, external conferences, and peer-reviewed publications, translating complex technical concepts for both technical and non-technical audiences
• Collaborate with domain experts such as medical professionals, bioinformaticians, and statisticians to guide and refine R&D efforts in AI-driven medical diagnostics and therapeutics

Preferred Qualifications

• Experience with therapeutics machine learning experience in oncology or immunology is a plus
• Experience with medical imaging and joint modeling of cancer genomics and imaging is a plus

Benefits

• Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents
• Free testing in addition to fertility care benefits
• Pregnancy and baby bonding leave
• 401k benefits
• Commuter benefits
• A generous employee referral program