Lead Machine Learning and Bioinformatics Scientist

Natera
San Carlos, CAPosted 26 March 2026

Job Description

LOCATION: Position is available as a hybrid position in San Carlos, Bay Area, California as well as a remote position within the US. Natera is currently seeking a highly skilled and innovative Lead Machine Learning Scientist to contribute to cutting-edge research and development within our Bioinformatics Research and Development team, focused on Epigenomics in Oncology. Natera’s mission is to change the management of disease worldwide by using information gained from a simple blood draw to detect disease early and proactively inform treatment. The ideal candidate will have a strong background in machine learning and statistical pattern recognition, as well as genomics and sequencing data analysis, with experience applying both classical and modern machine learning methods to large-scale biological data. This individual will play a critical role in developing, validating, and advancing state-of-the-art machine learning approaches for cancer detection and monitoring. PRIMARY RESPONSIBILITIES: Design, implement, and validate cutting-edge machine learning and statistical methods to solve problems in cancer diagnostics Contribute to best practices in model interpretability, uncertainty estimation, and reproducibility Design robust feature engineering and extraction pipelines tailored to biological data Prototype and productionize models using scalable ML infrastructure tools such as MLflow, Airflow, and Docker Collaborate closely with molecular biologists on experimental design, ensuring data integrity and quality control Foster a culture of innovation, collaboration, and scientific excellence Actively participate in code and design reviews QUALIFICATIONS: PhD in Computer Science, Machine Learning, Statistics, Bioinformatics, or a related quantitative field with a strong emphasis on cancer epi/genomics and 6+ years of experience post-PhD. Deep expertise in the theory and practical development of core machine learning models, including generalized linear models, kernel methods, tree-based algorithms, and neural networks, with a focus on biological data (e.g., DNA/RNA sequencing data) Proficiency in Python and its scientific computing stack (e.g., NumPy, Pandas, Scikit-learn) Strong cross-functional communication skills, with the ability to collaborate effectively across disciplines High scientific rigor and a growth mindset, with enthusiasm for both teaching and learning new computational and biological concepts Compensation Total Rewards This range reflects a good-faith estimate of the base pay we reasonably expect to offer at the time of hire. Final compensation will vary based on experience, qualifications, and internal equity considerations. This position is also eligible for additional compensation and benefits through Natera’s robust Total Rewards program, including: Annual performance incentive bonus Long-term equity awards Comprehensive health benefits (medical, dental, vision) 401(k) with company match Generous paid time off and company holidays Additional wellness and work-life benefits Compensation Range $144,000 $180,000 USD OUR OPPORTUNITY Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management. WHAT WE OFFER Competitive Benefits - Employee bene ... (truncated, view full listing at source)
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