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Biomedical Machine Learning Jobs in California (NOW HIRING)

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

Masimo

Engineer II, AI/Machine Learning

Irvine, CA

$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

Intuitive

Staff Machine Learning Engineer

Sunnyvale, CA · On-site

D. in Computer Science, Electrical Engineering, Robotics, Biomedical Engineering, Applied Mathematics, or a closely related field, with graduate training involving computer vision, machine learning ...

Intuitive

Staff Machine Learning Engineer

Sunnyvale, CA · On-site

D. in Computer Science, Electrical Engineering, Robotics, Biomedical Engineering, Applied Mathematics, or a closely related field, with graduate training involving computer vision, machine learning ...

BigHat

Principal, Machine Learning Scientist

San Mateo, CA · On-site

$254 - $290/hr

Principal, Machine Learning Scientist Department: DS/ML (Data Science/Machine Learning) Employment ... Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with ...

Intuitive

Sr. Machine Learning Engineer

Sunnyvale, CA · On-site

$143K - $189K/yr

MS or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field ... Machine Learning Practice (GMLP) principles, ensuring data representativeness and model ...

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Biomedical Machine Learning information

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.

What are the most commonly searched types of Biomedical Machine Learning jobs in California?

The most popular types of Biomedical Machine Learning jobs in California are:

What are popular job titles related to Biomedical Machine Learning jobs in California?

For Biomedical Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Biomedical Machine Learning jobs in California look for?

The top searched job categories for Biomedical Machine Learning jobs in California are:

What cities in California are hiring for Biomedical Machine Learning jobs?

Cities in California with the most Biomedical Machine Learning job openings:

Biomedical Machine Learning jobs near you
Infographic showing various Biomedical Machine Learning job openings in California 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.

Director, Machine Learning, Alzheimer's Disease Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
Arc Institute is an independent nonprofit research organization focused on artificial intelligence and biology, aiming to accelerate scientific progress in understanding complex diseases. The Director of Machine Learning for the Alzheimer's Disease Initiative will lead a team to develop sophisticated machine learning models to analyze neurodegeneration mechanisms and predict therapeutic interventions.
Responsibilities:
• Attract, build and lead a team of exceptional machine learning research scientists dedicated to developing foundation models for cellular systems in Alzheimer's disease
• Develop and execute on a roadmap of interpretable machine learning approaches to understand disease mechanisms, with emphasis on variational inference, causal modeling, as well as modern transformer- and diffusion-based architectures
• Work closely with experimentalists on brain organoid/spheroid cellular models as well as in vivo models, working with scRNA-seq, Perturb-seq and other datasets to unravel causal gene pathways relevant to Alzheimer’s disease
• Develop predictive modeling approaches to identify how perturbations can move cell states from high risk Alzheimer’s profiles back to healthy / low risk states
• Collaborate closely with experimental biologists to ensure ML models are grounded in disease biology and can feedback into future experimental strategies
• Foster collaborations with external partners in the computational biology and neuroscience communities
• Publish high-impact research through preprints, journal publications, open source code, and presentations at leading conferences
Qualifications:
Required:
• PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related quantitative field
• 7+ years of relevant experience with a minimum of 3 years of people management experience
• Strong research background with experience in academic settings (university, research institute) and/or biotech/pharmaceutical industry with a focus on scientific innovation
• Proven expertise in machine learning applications to biological datasets, with specific experience in single-cell profiling data and foundation model development
• Deep experience with interpretable machine learning approaches for biological systems (e.g. variational inference methods)
• Advanced technical skills in machine learning frameworks, particularly PyTorch, and ideally experience with model training at scale
• Publications in top-tier journals in computational biology and machine learning
• Excellent communication skills with ability to present complex machine learning concepts to both computational and biological audiences
• Proven ability to remain technically hands-on while providing effective team leadership, mentorship, and management
Preferred:
• Background in neurodegeneration research including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis is a plus
Company:
Arc Institute is a biomedical science and research technology company. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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