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Remote Biomedical Machine Learning Jobs in Oregon

Natera

Machine Learning Scientist, Multimodal AI

OR · On-site +1

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This ... Design, implement, and evaluate deep learning models across biomedical data modalities, including ...

FloVision Solutions

Machine Learning Engineer

OR · On-site +1

ABOUT FLOVISION FloVision is a remote-first startup focused on improving the food supply chain, starting with protein processing. We design computer vision and machine learning-assisted production ...

New

Blue River Technology

Machine Learning Engineer, Autonomy

OR · On-site +1

$113K - $202K/yr

Summary We are seeking a highly skilled and innovative Machine Learning Engineer to join the team ... Remote in the United States * Visa sponsorship : Open to visa sponsorship. Job Responsibilities A ...

New

Upstart

Senior Manager, Machine Learning

OR · On-site +1

The Team Our Core ML organization is looking for an exceptional, hands-on Machine Learning Manager ... US Remote Time Zone Requirements - This team operates on the East/West Coast time zones. Travel ...

Upstart

Staff/Principal Machine Learning Engineer

OR · On-site +1

As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and ... Remote-US Time zone requirements The team operates on the East/West coast time zones. Travel ...

Cresta

Staff Machine Learning Engineer

OR · On-site +1

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team ... Remote work setup budget to help you create a productive home office * Monthly wellness and ...

Cresta

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team ... Remote work setup budget to help you create a productive home office * Monthly wellness and ...

Liftoff

Staff Product Manager, Conversion ML

OR · On-site +1

... machine learning at scale is a plus. * Loads of passion for building great products and growing a great company! Location: Liftoff follows a philosophy of "remote first, come together meaningfully ...

Upstart

Applied Scientist

OR · On-site +1

The team conducts machine learning research, evaluates model performance, and partners closely with ... Remote Travel requirements As a digital first company, the majority of your work can be ...

Tebra

Data Engineer

OR · On-site +1

$114K - $137K/yr

You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to ... Remote

Upstart

Software Engineer, Verifications Platform

OR · On-site +1

Partner with Machine Learning, Product, Risk, Fraud, and Compliance teams to integrate data ... Remote Travel requirements As a digital first company, the majority of your work can be ...

Delaware Nation Industries

AI Developer/Engineer

OR · On-site +1

This is a fully-remote opportunity. The AI Developer/Engineer designs, develops, integrates, and supports production-ready artificial intelligence and machine learning solutions. This role works ...

Gnostech LLC

Software Engineer (US-Remote)

OR · On-site +1

US-Remote or Marlton, NJ area Description A Software Engineer is needed to design, develop, and ... Build and integrate AI-enabled capabilities into applications, including machine learning models ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... PRIMARY RESPONSIBILITIES * Hands-on development and write algorithms in machine learning ...

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Remote Biomedical Machine Learning information

What is a remote biomedical machine learning job?

Remote biomedical machine learning jobs involve applying machine learning and artificial intelligence techniques to biomedical data, such as medical images, genetic information, or clinical records, while working from a remote location. Professionals in these roles develop algorithms to assist in disease diagnosis, drug discovery, or patient outcome prediction. These jobs typically require strong programming skills, experience with data science tools, and a background in biomedical sciences or related fields. Remote positions offer flexibility and the ability to collaborate with interdisciplinary teams from anywhere in the world.

What are some unique challenges faced when working remotely as a biomedical machine learning professional, and how can they be addressed?

Remote Biomedical Machine Learning professionals often face challenges related to accessing large and sensitive datasets, ensuring compliance with data privacy regulations, and maintaining effective communication with interdisciplinary teams such as clinicians and researchers. To address these, it's important to become familiar with secure data transfer protocols, collaborate closely with IT and compliance officers, and utilize robust project management and communication tools. Regular virtual meetings and clear documentation can help bridge gaps and ensure alignment on project goals.

What are the key skills and qualifications needed to thrive as a remote biomedical machine learning specialist, and why are they important?

Thriving in Remote Biomedical Machine Learning requires expertise in machine learning, data analysis, and a strong background in biomedical sciences, often supported by an advanced degree in a related field. Proficiency with programming languages such as Python or R, experience with frameworks like TensorFlow or PyTorch, and familiarity with medical data systems are typically necessary. Excellent problem-solving skills, communication abilities, and self-motivation are standout soft skills for remote collaboration and research. These competencies are vital to effectively develop innovative biomedical solutions, ensure data integrity, and drive impactful research in a distributed work environment.

What is the difference between Remote Biomedical Machine Learning vs Remote Biomedical Data Analyst?

AspectRemote Biomedical Machine LearningRemote Biomedical Data Analyst
Required CredentialsMaster's or PhD in Bioinformatics, Data Science, or related fields; experience with ML frameworksBachelor's or Master's in Biology, Data Analysis, or related; proficiency in data visualization and statistical tools
Work EnvironmentCollaborative remote teams, research labs, tech companiesRemote healthcare organizations, research institutions, biotech firms
Employer & Industry UsageTech companies, biotech startups, research institutionsHospitals, healthcare providers, pharmaceutical companies

Remote Biomedical Machine Learning specialists focus on developing algorithms and models to analyze biomedical data, often requiring advanced degrees and programming skills. In contrast, Remote Biomedical Data Analysts interpret and visualize biomedical datasets, typically with a focus on statistical analysis. Both roles are vital in healthcare and biotech industries but differ in technical depth and responsibilities.

What are popular job titles related to Remote Biomedical Machine Learning jobs in Oregon?

For Remote Biomedical Machine Learning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Remote Biomedical Machine Learning jobs in Oregon look for?

The top searched job categories for Remote Biomedical Machine Learning jobs in Oregon are:

What cities in Oregon are hiring for Remote Biomedical Machine Learning jobs?

Cities in Oregon with the most Remote Biomedical Machine Learning job openings:

Remote Biomedical Machine Learning jobs near you

Machine Learning Scientist, Multimodal AI

Natera

OR • On-site, Remote

Full-time

Re-posted 23 days ago

Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

57th of 120 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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