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Biomedical Machine Learning Jobs in California (NOW HIRING)

Howard

Research Assistant

Seeley, CA · On-site

$24/hr

... biomedical and clinical sources. * Conduct exploratory data analysis , data visualization, and feature engineering. * Develop, train, and evaluate machine learning and deep learning models . * Review ...

Neuralink

Neuroengineer Intern

South San Francisco, CA · On-site

$35/hr

Evidence of exceptional ability in neuroscience, machine learning, biomedical engineering, or a related field * 2+ years of academic or industry experience * A strong understanding of the scientific ...

Ceribell, Inc

Data Scientist

Sunnyvale, CA · On-site

$184K - $210K/yr

We are looking for a talented data scientist/algorithm engineer who is passionate about biomedical applications and has a strong background in machine learning, pattern recognition, signal processing ...

Ceribell, Inc

Data Scientist

Sunnyvale, CA · On-site

$184K - $210K/yr

We are looking for a talented data scientist/algorithm engineer who is passionate about biomedical applications and has a strong background in machine learning, pattern recognition, signal processing ...

Fullpower Technologies

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

Connect biomedical sensor data with medical, health, and fitness outcomes * Research and development of machine learning algorithms and statistical models for non-invasive sleep tracking * Develop ...

Fullpower Technologies, Inc.

Data Scientist

Santa Cruz, CA · On-site

$130K - $170K/yr

Connect biomedical sensor data with medical, health, and fitness outcomes * Research and development of machine learning algorithms and statistical models for non-invasive sleep tracking * Develop ...

Masimo

VP, Algorithm - AI

Irvine, CA · On-site

$254K - $320K/yr

Drive innovation in machine learning, signal processing, and modeling to advance Masimo ... D.) in Biomedical Engineering, Electrical Engineering, Computer Science, or related field * Track ...

Masimo

VP, Algorithm - AI

Irvine, CA · On-site

$254K - $320K/yr

Drive innovation in machine learning, signal processing, and modeling to advance Masimo ... D.) in Biomedical Engineering, Electrical Engineering, Computer Science, or related field * Track ...

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Biomedical Machine Learning information

What is a Biomedical Machine Learning job?

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 typical day look like for someone in a Biomedical Machine Learning role?

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 the Biomedical Machine Learning position, 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 July 2026, with employment types broken down into 2% Internship, 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.
Associate Director/Principal, Machine Learning Scientist

Associate Director/Principal, Machine Learning Scientist

BigHat Biosciences

San Mateo, CA • On-site

Full-time

Posted 7 days ago

Job description

Job Summary:
BigHat Biosciences is seeking a creative, accomplished Associate Director or Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design. The role involves designing and implementing generative models, providing leadership and mentorship, and collaborating with interdisciplinary teams to enhance the company's antibody drug development platform.
Responsibilities:
• Design and implement the next state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties, trained on proprietary internal datasets of thousands to millions of antibodies.
• Provide leadership, technical guidance, and mentorship to other ML and data science FTEs and interns.
• Help set strategy for future ML research, driven by a strong high-level understanding of BigHat programs and operations as well as real-world drug development challenges.
• Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
• Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems for validation and deployment in our high-throughput wet lab - at BigHat success is only declared upon synthesis of real antibodies with drug-like properties.
• Maintain an in-depth understanding of the current state-of-the-art in ML-driven protein engineering, both in the literature and at BigHat.
• Share your findings at top-tier conferences and publish in leading scientific journals to advance the field of protein engineering.
• Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
• Collaborate with our engineering team to ensure maximal efficiency in the automated and agentic deployment of our latest models to our therapeutics programs.
• Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in BigHat’s platform, and plan and prioritize ML methods development accordingly.
Qualifications:
Required:
• PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background.
• Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry.
• Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices.
• Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
• Enjoys a fast-paced environment and excels at executing across multiple projects.
• Familiarity with the current state-of-the-art in ML-driven protein engineering.
Preferred:
• Experience with de novo design
• NGS data
• Bayesian optimization
• Familiarity with antibody biology and drug development
• Experience training and deploying models on AWS
Company:
BigHat Biosciences is a protein therapeutics company that develops an antibody design platform guided by artificial intelligence. Founded in 2019, the company is headquartered in San Mateo, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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