Senior Machine Learning Scientist - Multimodal AI

Natera is a global leader in cell-free DNA (cfDNA) precision medicine and genetic diagnostics across oncology, women’s health, and organ health. Our goal is to make personalized genetic testing and tumor-informed minimal residual disease (MRD) monitoring part of the standard of clinical care.

As a Machine Learning Scientist on our AI and Computational Biology team, you will develop and deploy state-of-the-art deep learning architectures across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. Operating at the intersection of AI, oncology, and multi-omics, you will build multimodal AI systems that combine whole-slide H&E imaging with proprietary molecular and clinical datasets. You will partner closely with pathologists, bioinformaticians, and software engineers to scale PyTorch workflows on AWS cloud infrastructure, translating research models into validated diagnostic tools.

Key Responsibilities

• Multimodal AI Architecture: Design, implement, and evaluate deep learning models that integrate H&E whole-slide imaging (WSI) data with genomic sequencing, transcriptomics, methylation, and cfDNA features.
• Model Development & Fine-Tuning: Apply advanced deep learning techniques—including Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), sequence transformers, representation learning, and foundation model adaptation.
• Production Pipeline Engineering: Build scalable, production-quality machine learning workflows and automated pipelines using PyTorch and distributed cloud infrastructure (AWS).
• Cross-Functional Collaboration: Partner with research scientists, clinical pathologists, and software engineers to translate experimental machine learning prototypes into validated production software.
• Clinical & Biological Insight Generation: Analyze model embeddings, feature attributions, and predictions to extract reproducible biological mechanisms and clinical diagnostic insights.
• Documentation & Communication: Thoroughly document model architectures, pipeline specs, and validation results while presenting data-driven findings to technical and clinical stakeholders.

Requirements

Academic & Machine Learning Background

• Ph.D. in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative technical field with a direct research focus on artificial intelligence or machine learning.
• Biomedical ML Expertise: Core experience developing machine learning models for biomedical applications, specifically in medical imaging, digital pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics.
• Software & Framework Proficiency: Advanced, production-level programming skills in Python and hands-on expertise with PyTorch.
• Deep Learning Depth: Practical application of modern deep learning architectures (CNNs, transformers, attention mechanisms, representation learning, and foundation model fine-tuning).
• Cloud Workflows: Experience managing multi-modal datasets and model training pipelines in cloud/distributed environments (AWS).
• End-to-End Ownership: Demonstrated ability to lead research projects independently and translate prototypes into deployment-ready, robust workflows.

Work Logistics

• Ability to work remotely within the United States.

Preferred Qualifications

• Experience building unified multimodal ML frameworks integrating whole-slide imaging (WSI), molecular assays, and longitudinal clinical data.
• Hands-on experience with digital pathology analysis software and weakly supervised learning frameworks (e.g., Multiple Instance Learning / MIL).
• Technical familiarity with DNA sequencing, RNA sequencing, methylation profiling, and circulating tumor DNA (ctDNA) assays.
• Experience with survival analysis, time-to-event modeling, or self-supervised learning algorithms.
• Track record of peer-reviewed publications in premier machine learning or computational biology venues (e.g., NeurIPS, ICML, CVPR, MICCAI, Nature Biomedical Engineering).

Total Rewards & Benefits

• Compensation: Base salary range of $124,800 – $171,600 USD benchmarked by role and geographic location.
• Healthcare & Wellness: Comprehensive medical, dental, vision, life, and disability plans for eligible employees and dependents.
• Family & Health Perks: Free genetic testing for employees and immediate family members, fertility care benefits, paid pregnancy leave, and baby bonding leave.
• Retirement & Perks: 401(k) retirement plan, pretax commuter benefits, and an employee referral bonus program.