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Machine Learning Biomedical Engineer Jobs in Sonoma, CA

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

D.) in computer science or a related field-such as artificial intelligence, computational neuroscience, or biomedical engineering-and at least three years of experience in machine learning research ...

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

Stackruit Ltd.

Machine Learning

San Francisco, CA · On-site

$200 - $250/hr

First Machine Learning Engineer (US Remote - $200k-$250k) Do you dream of using machine learning to empower businesses to take action on their data? Join a mission-driven company! About Us * We're ...

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$140 - $210/hr

Maintain, monitor, and enhance deployed machine learning systems to ensure continuous improvement. * Collaborate with software engineers, data scientists, and product teams to integrate AI solutions.

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML Platform team builds intelligent systems that power recommendations, forecasting, ranking ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Hive

Machine Learning Engineer

San Francisco, CA · 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 ...

Hive

Machine Learning Engineer

San Francisco, CA · 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 ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

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 ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

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 ...

Quantcast

Machine Learning Engineer

San Francisco, CA · On-site

$151.30 - $178/hr

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 ...

Apple

Machine Learning FEA Engineer

San Francisco, CA · On-site

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 ...

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All JobsMachine Learning Biomedical Engineer JobsMachine Learning Biomedical Engineer Jobs in Sonoma, CA

Machine Learning Biomedical Engineer information

See Sonoma, CA salary details

$35.3K

$144.3K

$216.8K

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

As of Aug 23, 2026, the average yearly pay for machine learning biomedical engineer in Sonoma, CA is $144,285.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,700.00 and $173,700.00 per year, depending on experience, location, and employer.

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.

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 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.

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 cities near Sonoma, CA are hiring for Machine Learning Biomedical Engineer jobs?

Cities near Sonoma, CA with the most Machine Learning Biomedical Engineer job openings:

Machine Learning Biomedical Engineer jobs near you
Infographic showing various Machine Learning Biomedical Engineer job openings in Sonoma, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $144,285 per year, or $69.4 per hour.

Machine Learning Researcher

Alljoined

San Francisco, CA • On-site

$140K - $250K/yr

Full-time

Medical

Re-posted 19 days ago

Job description

About Alljoined
Alljoined is creating a future where humans are fully understood and augmented by technology. Our work solves the communication bottleneck between humans and computers by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale neural datasets to decode internal thought directly. By advancing the frontier of neural decoding, we aim to unlock meaningful breakthroughs in human wellness and capability.
About the Role
We are looking for a talented Machine Learning Researcher to join our core R&D team. You will design and implement advanced machine learning models for EEG-based neural decoding, contribute to high-impact research, and help build the foundational infrastructure behind our brain-decoding systems.
You will work closely with leading experts in neural decoding and AI to push the boundaries of what is possible in brain-computer interfaces. This role sits at the intersection of ambitious research and rigorous engineering: you will explore novel modeling approaches while translating promising ideas into reliable, production-quality systems.
What You'll Work On
  • Develop, train, and refine state-of-the-art deep learning models for neural decoding, drawing on recent advances in architectures such as transformers and diffusion models.
  • Explore novel methods for modeling high-frequency, time-series EEG data alongside several adjacent data modalities.
  • Translate research insights into production-grade code that integrates seamlessly with our in-house BCI stack.
  • Collaborate with neuroscientists and machine learning engineers to build scalable, end-to-end neural-decoding systems.
  • Publish findings at leading machine learning and AI conferences, including NeurIPS, ICML, ICLR, and CVPR.
  • Contribute to open-source communities where appropriate.
You May Be a Good Fit If You Have
  • A bachelor's degree in computer science or a related field-such as artificial intelligence, computational neuroscience, mathematics, or biomedical engineering-and five to seven years of experience in machine learning research or applied machine learning engineering; or
  • A graduate degree (M.S. or Ph.D.) in computer science or a related field-such as artificial intelligence, computational neuroscience, or biomedical engineering-and at least three years of experience in machine learning research or applied machine learning engineering.
  • A track record of high-quality research, demonstrated through publications at leading machine learning conferences or in respected journals, including NeurIPS, ICML, ICLR, or CVPR.
  • Strong proficiency in Python and PyTorch, along with familiarity with modern machine learning tooling and distributed training.
  • Experience contributing to a production-quality codebase with modern code-review standards.

Candidates with a Ph.D. and/or experience working in a high-profile machine learning research lab are strongly preferred.
Areas of Relevant Expertise
We are particularly interested in candidates with experience in one or more of the following areas:
  • Multimodal representation learning: CLIP-style contrastive objectives and masked autoencoding.
  • Generative modeling: Diffusion models, transformer decoders, and latent GANs.
  • Temporal sequence modeling: State-space models, STFT-aware transformers, and RWKV.

Compensation Range
$140,000 - $250,000/year + equity
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range.
Benefits
  • Options for housing support
  • Visa sponsorship
  • Health insurance

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