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Assistant Medical Imaging Machine Learning Jobs in Oregon

Natera

OR

Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular ...

Vectara

Machine Learning (ML) Engineer

OR · On-site +1

Vectara provides a scalable platform to deploy your Enterprise AI Agents and AI Assistants with ... Perks and Benefits: 100% paid Medical, Dental, Vision begins on your first day! Option of Health ...

Natera

OR

... digital pathology imaging, and longitudinal clinical metadata * Design rigorous clinical ... Partner with Computational Biology, Translational Science, and Medical Affairs teams to translate ...

Aptive

$25.25 - $33.50/hr

... Medical Imaging Systems to support the Department of Veterans Affairs (VA) under the Biomedical ... . * Assist with equipment lifecycle management including installation planning, upgrades ...

Anno.ai

OR

$104K - $143K/yr

We actively monitor for synthetic profiles, proxy networks, and AI interview assistants; any ... Position Overview As a Senior Machine Learning Engineer at Anno.ai, you will design, develop, test ...

OptiTrack

Machine Learning & Operations Engineer

Corvallis, OR · Remote

$72K - $97K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale ... medical for employee. Family coverage also included. * 100% employer paid dental, and vision for ...

OptiTrack

Machine Learning & Operations Engineer

Corvallis, OR · Remote

$72K - $97K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale ... medical for employee. Family coverage also included. * 100% employer paid dental, and vision for ...

Natera

Staff Machine Learning Scientist, Agentic AI

OR · On-site +1

Natera is seeking a Staff Machine Learning Scientist - Agentic AI to join our AI team, an advanced ... imaging modalities for multi-step biological reasoning and tool use * Implement advanced LLM ...

Trimble

Machine Learning Data Scientist

Lake Oswego, OR · On-site

$122K - $165K/yr

In this role, you will be at the forefront of developing predictive machine learning models ... Trimble offers comprehensive core benefits that include Medical, Dental, Vision, Life, Disability ...

Cresta

OR

Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center ... Comprehensive medical, dental, and vision coverage with plans to fit you and your family * Flexible ...

Cresta

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center ... Comprehensive medical, dental, and vision coverage with plans to fit you and your family * Flexible ...

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Assistant Medical Imaging Machine Learning information

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Assistant Medical Imaging Machine Learning jobs near you

Machine Learning Scientist, Multimodal AI

Natera

OR

Other

Posted 29 days ago

Natera rating

7.7

Company rating: 7.7 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

50th of 103 rated laboratories

Job description

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)

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