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Machine Learning Biomedical Engineer Jobs (NOW HIRING)

Latent

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two ... Experience working with clinical, biomedical, or other regulated datasets Why Join Latent Health

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

About the Role We're seeking a talented Machine Learning Researcher to join our core R&D team. This ... Neuroscience, Mathematics, Biomedical Engineering, etc), with 5-7 years of experience in ML ...

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site +1

$140K - $250K/yr

About the Role We're seeking a talented Machine Learning Researcher to join our core R&D team. This ... Neuroscience, Mathematics, Biomedical Engineering, etc), with 5-7 years of experience in ML ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ... D. degree in Electrical Engineering, Biomedical Engineering, or a related field required ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ... D. degree in Electrical Engineering, Biomedical Engineering, or a related field required ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA

$140K - $170K/yr

Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ... D. degree in Electrical Engineering, Biomedical Engineering, or a related field required ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ... D. degree in Electrical Engineering, Biomedical Engineering, or a related field required ...

Harvard University

Machine Learning Engineer

Boston, MA · On-site

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 ...

Harvard University

Machine Learning Engineer

Boston, MA · On-site +1

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 ...

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All JobsMachine Learning Biomedical Engineer Jobs

Machine Learning Biomedical Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Jun 4, 2026, the average yearly pay for machine learning biomedical engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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 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 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.

More about Machine Learning Biomedical Engineer jobs
What cities are hiring for Machine Learning Biomedical Engineer jobs? Cities with the most Machine Learning Biomedical Engineer job openings:
What states have the most Machine Learning Biomedical Engineer jobs? States with the most job openings for Machine Learning Biomedical Engineer jobs include:
What job categories do people searching Machine Learning Biomedical Engineer jobs look for? The top searched job categories for Machine Learning Biomedical Engineer jobs are:
Machine Learning Biomedical Engineer jobs near you
Infographic showing various Machine Learning Biomedical Engineer job openings in the United States as of May 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Temporary. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Latent

San Francisco, CA • On-site

$225K - $300K/yr

Full-time

Posted 29 days ago

Job description

Machine Learning Engineer
About Latent Health
Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family.
For everyone else, care is fragmented and impersonal.
Medical history is scattered across systems that don't communicate. Physicians have minutes to understand decades of context. And when something goes wrong, patients are left with tools that understand medicine broadly-but not the individual.
We believe this can be fundamentally rebuilt.
At Latent Health, we are building systems that understand both:
  • the population (clinical knowledge at scale)
  • and the individual (longitudinal patient history)

Our models are designed to answer complex clinical questions with patient-specific context and verifiable reasoning.
Our dataset represents one of the most clinically diverse populations in the United States, including patients with chronic illness and complex disease. Each patient record contains extraordinary depth.
ML at Latent Health
The Machine Learning team is responsible for building systems that run in real clinical workflows.
We work on:
  • Verifiable reinforcement learning at scale
  • Mid-training and post-training of foundation models
  • Novel objectives derived from longitudinal patient data

We are a small group of researchers and engineers focused on pushing the frontier while shipping real systems into production.
We are a small team and expect engineers to take ownership of critical systems, not components.
The Role
As a Machine Learning Engineer, you will own the design, development, and operation of production-grade ML systems that run in real clinical workflows.
You will drive systems from ambiguous problem definition through to reliable production deployment, setting technical direction along the way.
We are primarily hiring for senior and staff-level engineers who are comfortable owning critical systems end-to-end.
This role involves owning systems that directly impact real patient outcomes.
What You'll Do
  • Own end-to-end ML systems, including architecture, data, modeling, evaluation, and production infrastructure
  • Train and fine-tune large language models (LLMs) for:
    • Clinical reasoning
    • Medical question answering
    • Evidence-grounded generation
  • Make and own tradeoffs across accuracy, latency, cost, and safety in high-stakes production environments
  • Develop evaluation frameworks to ensure model safety and clinical validity
  • Integrate ML systems into product workflows and patient-facing applications
  • Monitor system performance in production and iterate based on real-world usage and feedback
  • Define what "correct" means in ambiguous clinical workflows in collaboration with engineers and clinicians

What We're Looking For
  • Strong foundation in machine learning and software engineering
  • Track record of building and owning ML systems in production where performance, reliability, or correctness materially mattered
  • Experience driving ambiguous ML problems from 0→1, including problem formulation, model design, and productionization
  • Hands-on experience with PyTorch or similar frameworks
  • Ability to operate independently in high-ambiguity environments with minimal guidance
  • Strong product and engineering judgment - you know when to use ML, when not to, and how to scope problems accordingly
  • Comfort working in a fast-moving, early-stage environment
  • Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure)

Nice to Have
  • Experience deploying LLMs in production environments
  • Experience building distributed systems or large-scale data pipelines
  • Experience working with clinical, biomedical, or other regulated datasets

Why Join Latent Health
  • Work on high-stakes problems with real impact on patient care
  • Build systems that define how AI is trusted in clinical decision-making
  • Significant ownership in a small, high-caliber team
  • Competitive compensation and meaningful equity

Location
We are based in San Francisco and work together in person.
We spend most of the week in the office and prioritize candidates who are excited to work this way.
Compensation
  • Base salary: $225,000 - $300,000+
  • Meaningful equity in an early-stage, Series A company

Closing
If you're interested in building systems that bring truly personalized healthcare to millions of patients, we'd love to talk.

Apply