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Machine Learning Biomedical Engineer Jobs in Boston, MA

You'll be at the heart of biomedical discovery, education, and innovation, working alongside world ... Machine Learning Engineer with advanced expertise to lead development of large language models ...

You'll be at the heart of biomedical discovery, education, and innovation, working alongside world ... Machine Learning Engineer with advanced expertise to lead development of large language models ...

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new ...

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting-edge machine ...

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting-edge machine ...

PhD in machine learning, computer vision, medical image analysis, biomedical engineering, or related field * Strong publication record in relevant venues (medical imaging, clinical ML, computer ...

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Machine Learning Biomedical Engineer information

See Boston, MA salary details

$34.2K

$139.9K

$210.2K

How much do machine learning biomedical engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for machine learning biomedical engineer in Boston, MA is $139,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,300.00 and $168,400.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What does a Machine Learning Biomedical Engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

What are the key skills and qualifications needed to thrive as a Machine Learning Biomedical Engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

How does a Machine Learning Biomedical Engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.
What are popular job titles related to Machine Learning Biomedical Engineer jobs in Boston, MA? For Machine Learning Biomedical Engineer jobs in Boston, MA, the most frequently searched job titles are:
Group 2-24 | Co-Op | Biomedical & Physiological Signal Processing & Machine Learning | Jun-Dec 2026

Group 2-24 | Co-Op | Biomedical & Physiological Signal Processing & Machine Learning | Jun-Dec 2026

MIT Lincoln Laboratory

Lexington, MA

$21.50 - $25/hr

Other

Posted 11 days ago


Job description

The Human Health & Performance Systems Group develops human-centered technologies to overcome operational challenges and to enhance human capability in domains of interest to national security. Our research programs focus on innovative and objective solutions in the areas of integrated wearable systems, human-machine teaming, enhanced communications, neurocognitive analytics, and medical technologies. Our group is highly interdisciplinary and includes scientific experts in physiology, cognitive science, neuroscience, psychology, biomechanics, computer science, engineering, and physics. Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.

Position Description

Our team is looking for a Co-Op student with an interest in solving challenging AI/ML problems using biomedical signal processing and wearable technology. Through this opportunity, you will work with a multi-disciplinary team

consisting of engineers, scientists, and clinicians to prepare and process large biomedical and physiological datasets (e.g.,PPG, accelerometry, EOG, EEG, commercial-off-the-shelf wearable data, etc), develop and evaluate machine learning algorithms, and implement data visualization tools for advanced prediction and inference of physiological status (i.e. fatigue, illness, stress, etc). We are looking for students who are self-motivated

and interested in signal processing, machine learning, deep learning, statistical pattern recognition, and high-performance computing.

Requirements/Skills

  • The candidate is a student in a B.S., M.S., or Ph.D. program in Biomedical Engineering, Electrical Engineering, Computer Science, or other relevant degree.
  • Experience with Python, MATLAB and machine learning (coursework or practical)

Preferred (not required)

  • Biomedical signal processing and/or time series analysis experience
  • Experience with Python and deep learning libraries like: Pytorch, JAX, and/or keras
  • Interest in AI meta-learning, foundation models / self-supervised learning, continual learning, one-shot and/or transfer learning

Compensation for 2026

  • Technical Co-Op: $24.50 - $31.00 per hour (based on year in school)
  • Administrative Co-Op: $21.50 - $25.00 per hour (based on year in school)

Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.

MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.