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Machine Learning Biomedical Engineer Jobs in Berkeley, CA

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Machine Learning Engineer

San Francisco, CA ยท On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Machine Learning Engineer

San Francisco, CA ยท On-site

$151K - $178K/yr

As a Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof ...

As a Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof ...

We are committed to pushing the boundaries of innovation and engineering excellence in product designs through machine learning and FEA simulations. We truly believe in the power of predictive ...

The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Machine Learning Engineer

San Francisco, CA ยท On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Machine Learning Engineer

San Francisco, CA ยท On-site

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

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Machine Learning Biomedical Engineer information

See Berkeley, CA salary details

$38.6K

$157.7K

$236.9K

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

As of Jun 28, 2026, the average yearly pay for machine learning biomedical engineer in Berkeley, CA is $157,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,300.00 and $189,800.00 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 Berkeley, CA? For Machine Learning Biomedical Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biomedical Engineer jobs in Berkeley, CA look for? The top searched job categories for Machine Learning Biomedical Engineer jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Machine Learning Biomedical Engineer jobs? Cities near Berkeley, CA with the most Machine Learning Biomedical Engineer job openings:

Machine Learning Engineer

PhysicsX

San Francisco, CA โ€ข On-site, Remote

Other

Medical, Retirement, PTO

Posted 25 days ago


Job description

Note:ย We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.

Who We're Looking For

As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

We have hybrid offices in London, New York, and Singapore; this role is hybrid based in the San Francisco area.

This Roleย 

As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.

What you will do
  • Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
  • Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
  • Explore and manipulate 3D point cloud & mesh data
  • Own the delivery of technical workstreams
  • Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
  • Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
  • Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
  • Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption
You'll also have the opportunity to travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
ย 
What you bring to the table
  • Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings.
  • Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged.
  • A track record of scoping and delivering projects in a customer facing role
  • 2+ years' experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
  • Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
  • Distributed computing frameworks (e.g., Spark, Dask)
  • Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
  • Containerization and orchestration (Docker, Kubernetes)ย ย ย 
  • Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
  • Excellent collaboration and communication skills - with teams and customers alike
  • A background in Physics, Engineering, or equivalent
Our delivery teams drive innovation to turn AI models into practical solutions -ย read our blog to learn more about how you'll contribute to this exciting journey! What we offerBuild what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected.

And it doesn't stop there ...

ย Equity optionsย - share meaningfully in the company you're helping to build.

ย 5% contribution toย 401(k)ย - build long-term security with a strong retirement plan.

ย Private health insuranceย - comprehensive cover for you, offering total peace of mind.

ย Enhanced parental leaveย - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

ย 20 days of Annual Leave (+ Public Holidays)ย - because taking time to rest matters.

ย Personal developmentย - dedicated support for learning, development, and leveling up over time.

ย Gympass / Wellhub (subsidized)ย - for you and up to 3 family members, supporting both physical and mental wellbeing.

ย Flexible Spending Account (FSA)ย - set aside pre-tax dollars for eligible healthcare expenses.

Watch this space, we're continuing to build this as we grow...

Salary range:

$150,000 - $190,000 depending on experienceย 
Seniority will be assessed throughout our interview processย