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Biomedical Machine Learning Jobs (NOW HIRING)

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA

$140K - $170K/yr

Responsible for algorithm design, development, implementation, testing, and documentation for Biomedical Signal Processing systems * Design, train and evaluate machine learning models using large ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Responsible for algorithm design, development, implementation, testing, and documentation for Biomedical Signal Processing systems * Design, train and evaluate machine learning models using large ...

Masimo

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and ... Experience in applying AI/ML to biomedical data * Experience with computer vision and/or robotics

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How much do biomedical machine learning jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for biomedical machine learning in the United States is $28.53, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $32.21 per hour, depending on experience, location, and employer.

What is a biomedical machine learning?

A Biomedical Machine Learning job involves developing and applying machine learning algorithms to analyze biomedical data for healthcare and research applications. Professionals in this field work with medical imaging, genomics, electronic health records, and wearable device data to improve disease diagnosis, treatment, and patient outcomes. They collaborate with researchers, clinicians, and data scientists to design predictive models and extract insights from complex biological data. This role requires expertise in machine learning, data processing, and domain-specific knowledge in healthcare or life sciences.

What does a biomedical machine learning do?

A typical day in Biomedical Machine Learning involves cleaning and preparing biomedical datasets, developing or refining machine learning models, running experiments, and interpreting results in collaboration with domain experts such as bioinformaticians and clinicians. Professionals often participate in team meetings to discuss project goals, share insights, and adjust research directions based on feedback. The role may also involve reading scientific literature to stay current with new methodologies and contributing to academic publications or technical documentation. Working closely with both technical and healthcare-focused colleagues, you'll help translate data-driven insights into meaningful biomedical solutions that impact patient care or research outcomes.

What are the key skills and qualifications needed to thrive in biomedical machine learning, and why are they important?

To thrive in Biomedical Machine Learning, you need a solid background in statistics, machine learning, programming (Python or R), and a strong understanding of biological or medical data, often supported by advanced degrees in computer science, biomedical engineering, or related fields. Experience with frameworks like TensorFlow, PyTorch, and familiarity with biomedical datasets is highly valued, and certifications in data science or biomedical informatics can be advantageous. Strong analytical thinking, communication skills, and the ability to collaborate with interdisciplinary teams are crucial soft skills. These competencies are vital to developing robust models that address complex healthcare challenges while ensuring scientific rigor and regulatory compliance.

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Biomedical Machine Learning jobs near you
Infographic showing various Biomedical Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $59,333 per year, or $28.5 per hour.

Postdoctoral Fellows - Computational Biology & Machine Learning

The Henry M. Jackson Foundation for the Advancement of Military Medicine

Bethesda, MD • On-site

$52K - $71K/yr

Full-time

Posted 6 days ago

Job description

Job Summary:
The Henry M. Jackson Foundation for the Advancement of Military Medicine is a nonprofit organization dedicated to advancing military medicine. They are seeking a Postdoctoral Fellow in Computational Biology & Machine Learning to lead innovative research projects and develop AI/ML tools for cancer genomics analysis.
Responsibilities:
• Lead Innovative research. Conceive and execute computational research projects, develop novel algorithms and analytical frameworks to interrogate large-scale, multidimensional omics datasets, and translate findings into clinically meaningful insights. Motivation to lead research projects under Principal Investigator’s supervision.
• Build Artificial Intelligence (AI)/Machine Learning (ML) tools. Design, implement, document, and publicly release AI/ML models - including deep learning approaches - for integrative analysis of cancer genomic data, contributing resources that advance the broader scientific community.
• Engineer scalable pipelines. Develop and maintain robust, reproducible computational pipelines for processing, integrating, and managing complex biomedical datasets across multiple data modalities.
• Drive scientific communication. Lead and contribute to the preparation of high-impact scientific manuscripts, grant and fellowship applications, and conference presentations; represent the lab at national and international scientific meetings.
• Collaborate across disciplines. Actively contribute to team meetings and foster a culture of scientific excellence within a diverse, interdisciplinary research environment.
Qualifications:
Required:
• A PhD in Bioinformatics, Computational Biology, Systems Biology, Quantitative Genomics, Biomedical Engineering, Machine Learning, Computer Science (with a computational biology focus), or a closely related field is required.
• Candidates at all stages of their postdoctoral career (0–5 years of postdoctoral experience) are encouraged to apply.
• Strong foundation in statistical and computational modeling and data analysis applied to genomics questions is required.
• Experience with Artificial Intelligence (AI)/Machine Learning (ML) (deep learning) methods applied to cancer genomics is considered a strong asset.
• Demonstrated experience developing or applying computational or statistical pipelines to molecular, biological, clinical, or multi-omics data.
• Proficiency in Python, R, and/or C/C++, with hands-on experience using scientific computing libraries (e.g., pandas, NumPy, SciPy, scikit-learn, Bioconductor).
• Demonstrated experience building or applying computational/statistical pipelines to molecular, clinical, or multi-omics datasets.
• Proficiency with reproducible workflow management systems such as Snakemake, Nextflow, or equivalent pipeline frameworks.
• Familiarity with cloud or high-performance computing (HPC) environments, such as Google Cloud, Amazon AWS, SLURM/SGE-based clusters, or equivalent infrastructure.
• Experience applying AI/ML and deep learning methods to cancer genomics problems - particularly single-cell omics, spatial omics, epigenomics, or liquid biopsy fragmentomics is highly valued.
• Prior work with large-scale biomedical datasets, including multi-omics, single-cell, spatial, clinical genomics, or treatment-response data is highly valued.
• A track record of peer-reviewed publications commensurate with career stage in computational biology, bioinformatics, biomedical data science, or related fields is highly valued.
• Proven ability to collaborate effectively within large, interdisciplinary teams.
• Strong organizational skills with the ability to manage multiple priorities and meet deadlines in a fast-paced research environment.
• Excellent written and verbal communication skills in English, including demonstrated scientific writing ability.
• Ability to obtain and maintain a T1/Public Trust background check.
• Ability to stand or sit at a computer for prolonged periods.
Company:
The Henry M. Founded in 1983, the company is headquartered in Bethesda, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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