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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 ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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 ...

Cellanome

Machine Learning Engineer

Foster, OR · On-site +1

$160K - $215K/yr

The Machine Learning Engineer will work in close collaboration with the core instrument, assay and ... Possibility for Remote. Key Responsibilities: * Design, develop, and optimize advanced algorithms ...

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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

OR • On-site, Remote

Natera
Biotechnology Research and Development • 1 - 5K employees
Learn more about Nateraexternal

Full-time

Re-posted 14 days ago

Natera rating

7.8

Company rating: 7.8 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

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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