Machine Learning Scientist, Multimodal 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 aims to make personalized genetic testing and diagnostics part of standard medical care, enabling earlier and more targeted interventions that help people live longer, healthier lives.

Natera brings together professionals across statistics, genetics, medicine, laboratory science, software engineering, and other disciplines to advance disease detection and management.

About the Role

Natera is seeking a Machine Learning Scientist to join its AI and computational biology team. This remote position focuses on developing and deploying deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA data to advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing.

The scientist will build multimodal AI systems that combine imaging, molecular, and clinical information from proprietary genomic and clinical datasets. Working closely with scientists, pathologists, bioinformaticians, and software engineers, the successful candidate will help turn machine learning research into scalable, validated, and production-ready tools for clinical applications.

Key Responsibilities

• Design, implement, and evaluate deep learning models across biomedical data types, including histopathology images, genomic sequencing, transcriptomics, and cfDNA features.
• Develop multimodal AI architectures that integrate hematoxylin and eosin (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.
• 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 applying deep learning architectures, including CNNs, transformers, attention mechanisms, and representation learning.
• Experience managing datasets and training workflows in distributed or cloud computing environments, including AWS.
• Demonstrated ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows.
• Experience adapting pretrained 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.
• Peer-reviewed publications in machine learning or computational biology conferences and journals, such as NeurIPS, ICML, CVPR, MICCAI, or Nature Biomedical Engineering.

Salary and Benefits

The advertised base salary range for this remote U.S. position is $124,800–$156,000 USD. Actual compensation depends on several factors, including skills, depth of experience, certifications, and work location. Compensation may vary across locations due to differences in labor costs.

Natera offers a range of benefits for eligible employees and their dependents, including:

• Comprehensive medical, dental, vision, life, and disability insurance.
• Free testing for employees and their immediate families.
• Fertility care benefits.
• Pregnancy and baby-bonding leave.
• 401(k) benefits.
• Commuter benefits.
• Employee referral program.

Work Arrangement and Location

• Location: Remote within the United States.
• Listed Location: Modesto, California.
• Team: AI and Computational Biology.

Equal Employment Opportunity

Natera is an Equal Opportunity Employer committed to building a diverse and inclusive workplace. All qualified applicants are 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. Qualified applicants are also considered regardless of criminal history, consistent with applicable laws.

Candidate Communication and Fraud Prevention

Natera communicates with candidates only through email addresses using the @natera.com domain. Messages from other domains claiming to represent Natera or its employees are fraudulent. The company does not conduct interview requests through text messages and does not request personal information until candidates have engaged with a recruiter and the hiring team. Natera takes cybercrime seriously and works with law enforcement to address related offenses.