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Machine Learning Scientist, Multimodal AI

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Remote from
USA
Salary
USD 124,800–171,600 / yr
Employment
Full Time
Experience
Senior
Published
Apply before
2 Dec 2026
Listing views
21
Application actions
2
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AI Summary

The role, at a glance.

Natera is seeking a Machine Learning Scientist to develop and deploy multimodal deep-learning systems for oncology diagnostics. The role combines digital pathology, genomics, transcriptomics, cfDNA, molecular, and clinical data to generate validated clinical insights. The scientist will build scalable AWS-based workflows and move research prototypes into production-ready tools with cross-functional clinical and engineering teams. Success requires doctoral-level machine learning expertise, strong Python and PyTorch skills, and experience with biomedical data and modern architectures such as CNNs, vision transformers, and foundation models.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThis is a highly specialized research-and-production role requiring deep expertise across machine learning, cloud workflows, and complex biomedical modalities. The candidate must independently translate research ideas into robust systems that support clinically meaningful diagnostics.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$148,200
US market range (per year)$135k–$195k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a USD 124,800–171,600 pay range. The annual cadence is inferred rather than explicitly stated, based on the range magnitude, US remote location, full-time context, and senior doctoral-level machine learning scope. The estimated US annual market range for a biomedical multimodal ML scientist is USD 135,000–195,000.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a multimodal model that integrates whole-slide pathology images with genomic and clinical data?

I would first define modality-specific preprocessing and quality-control pipelines, then train dedicated encoders for image tiles, molecular features, and structured clinical variables. I would evaluate late-fusion and cross-attention architectures, use patient-level aggregation for slide data, and validate performance through stratified external cohorts and clinically relevant endpoints.

What considerations are important when fine-tuning a foundation model for biomedical imaging?

I would assess domain shift between the pretraining data and target pathology data, use careful normalization and augmentation, and begin with parameter-efficient fine-tuning when data are limited. I would also monitor calibration, subgroup performance, interpretability, and leakage risks at the patient and site level.

How have you made machine learning workflows production-ready?

I use versioned data and code, reproducible environments, automated training and evaluation pipelines, model registries, and monitoring for data drift and performance degradation. I also define clear interfaces with engineering teams and document assumptions, validation results, and deployment constraints.

How would you evaluate a model intended to support oncology diagnostics?

I would establish clinically meaningful endpoints and compare against appropriate baselines, using patient-level splits and independent validation sets. Beyond discrimination metrics, I would evaluate calibration, sensitivity at relevant specificity thresholds, subgroup robustness, error modes, and the clinical implications of false-positive and false-negative predictions.

Describe how you communicate complex model findings to clinical and nontechnical stakeholders.

I focus on the clinical question, key evidence, limitations, and decision impact rather than model mechanics alone. I use concise visualizations, explain validation design and uncertainty clearly, and tailor the depth of technical detail to the audience while preserving scientific accuracy.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

POSITION SUMMARY:

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing.

PRIMARY 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 data with molecular and clinical data sources
  • Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS)
  • Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning
  • Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools
  • Analyze model outputs to generate reproducible biological and clinical insights
  • Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders

QUALIFICATIONS:

  • PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI
  • Core experience developing machine learning models for biomedical applications, specifically 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 application of deep learning architectures such as CNNs, transformers, attention mechanisms, and representation learning
  • Experience managing datasets and training workflows within distributed or cloud computing environments (AWS)
  • Proven 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 within unified multimodal machine learning frameworks
  • Technical familiarity with DNA sequencing, RNA sequencing, methylation, and ctDNA assays
  • Hands-on experience with digital pathology software and whole-slide imaging 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
  • Domain knowledge in oncology, biomarker discovery, or clinical precision medicine
  • Track record of peer-reviewed publications in machine learning or computational biology conferences and journals (e.g., NeurIPS, ICML, CVPR, MICCAI, Nature Biomedical Engineering)

The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.

Remote USA

$124,800—$171,600 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 benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!

For more information, visit www.natera.com.

Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.

All qualified applicants are encouraged to apply, and 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. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws.

If you are based in California, we encourage you to read this important information for California residents.

Link: https://www.natera.com/notice-of-data-collection-california-residents/

Please be advised that Natera will reach out to candidates with a @natera.com email domain ONLY. Email communications from all other domain names are not from Natera or its employees and are fraudulent. Natera does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. Natera takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes.

For more information:
– BBB announcement on job scams
– FBI Cyber Crime resource page

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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