Machine Learning Scientist, AI
About the Company
Natera is a global leader in cell-free DNA (cfDNA) testing, with a focus on oncology, women's health, and organ health. The company develops personalized genetic testing and diagnostic solutions intended to support earlier detection, more targeted interventions, and improved patient care. Natera's teams bring together statisticians, geneticists, physicians, laboratory scientists, software engineers, and other professionals to advance genetic disease management and personalized diagnostics.
About the Role
Natera is seeking a Machine Learning Scientist to join its AI and computational biology team. This role focuses on developing and deploying deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) data. You will build multimodal AI systems that combine imaging, molecular, and clinical information to support personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing. Working with scientists, pathologists, bioinformaticians, and software engineers, you will develop scalable machine learning workflows, adapt foundation models for biomedical applications, and translate research prototypes into validated, production-ready tools. The role also involves analyzing model outputs to generate reproducible biological and clinical insights and communicating findings to cross-functional stakeholders.
Key Responsibilities
Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features. Develop multimodal AI architectures that integrate H&E whole-slide imaging with molecular and clinical data. Build scalable, production-quality machine learning workflows and pipelines using AWS cloud infrastructure. Apply modern machine learning techniques, including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning. Collaborate with technical and clinical teams to translate machine learning prototypes into validated tools. Analyze model outputs to generate reproducible biological and clinical insights. Document machine learning pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders.
Required Qualifications
PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline, with a focus on machine learning or artificial intelligence. Core experience developing machine learning models for biomedical applications, particularly in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics. Hands-on expertise with PyTorch and strong production-level programming skills in Python. Practical experience with deep learning architectures, including CNNs, transformers, attention mechanisms, and representation learning. Experience managing datasets and training workflows in distributed or cloud computing environments, particularly AWS. Demonstrated ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows. Experience adapting pre-trained foundation models for downstream biomedical applications.
Preferred Qualifications
Experience integrating imaging, molecular, and clinical data into unified multimodal machine learning frameworks. Technical familiarity with DNA sequencing, RNA sequencing, methylation, and circulating tumor DNA (ctDNA) assays. Hands-on experience with digital pathology software and whole-slide image analysis. Exposure to survival modeling, longitudinal prediction, or time-to-event modeling. Experience applying self-supervised learning, weakly supervised learning, or multiple instance learning (MIL) to clinical data. Knowledge of oncology, biomarker discovery, or clinical precision medicine. A track record of peer-reviewed publications in machine learning or computational biology conferences and journals, such as NeurIPS, ICML, CVPR, MICCAI, or Nature Biomedical Engineering. Salary & Benefits The stated annual base pay range for this position is $124,800–$156,000 USD. Actual compensation may vary based on factors including skills, years and depth of experience, certifications, and work location. Compensation ranges may differ across locations due to labor market considerations. Benefits for eligible employees and their dependents include comprehensive medical, dental, vision, life, and disability plans. Free testing for Natera employees and their immediate families. Fertility care benefits. Pregnancy and baby bonding leave. 401(k) benefits. Commuter benefits. Employee referral program. Additional employee benefits and programs. Location and Work Arrangement This is a fully remote position open to candidates in the United States. Equal Employment Opportunity Natera is an Equal Opportunity Employer committed to maintaining a diverse and inclusive workplace. All qualified applicants will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability, or any other legally protected status. Natera also considers qualified applicants regardless of criminal history, consistent with applicable laws. Recruitment Security Notice Natera states that official recruiting communications will come only from email addresses using the @natera.com domain. The company does not conduct interviews through text messages or request personal information before candidates have engaged with a recruiter and the hiring team. Candidates should be cautious of communications from other domains claiming to represent Natera.