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Biomedical Machine Learning Jobs in Los Angeles, CA

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA

$140K - $170K/yr

Responsible for algorithm design, development, implementation, testing, and documentation for Biomedical Signal Processing systems * Design, train and evaluate machine learning models using large ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Responsible for algorithm design, development, implementation, testing, and documentation for Biomedical Signal Processing systems * Design, train and evaluate machine learning models using large ...

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 · 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

MiniMed

Principal Biomedical Engineer

Los Angeles, CA · On-site

... in this role will apply machine learning tools to improve upon current process monitoring ... This Principal Biomedical Engineer will partner cross functionally to highlight insights from real ...

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How much do biomedical machine learning jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for biomedical machine learning in Los Angeles, CA is $30.74, according to ZipRecruiter salary data. Most workers in this role earn between $26.15 and $34.71 per hour, depending on experience, location, and employer.

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 Los Angeles, CA?

The most popular types of Biomedical Machine Learning jobs in Los Angeles, CA are:

What are popular job titles related to Biomedical Machine Learning jobs in Los Angeles, CA?

For Biomedical Machine Learning jobs in Los Angeles, CA, the most frequently searched job titles are:

What job categories do people searching Biomedical Machine Learning jobs in Los Angeles, CA look for?

The top searched job categories for Biomedical Machine Learning jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Biomedical Machine Learning jobs?

Cities near Los Angeles, CA with the most Biomedical Machine Learning job openings:

Biomedical Machine Learning jobs near you
Infographic showing various Biomedical Machine Learning job openings in Los Angeles, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $63,932 per year, or $30.7 per hour.

Research Data Scientist - Urology, Hung Lab

West Hollywood, CA • On-site

Cedars Sinai
Hospitals • 10K+ employees

8.6

Company rating: 8.6 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

43rd of 1,063 rated hospitals

Great coworkers

People enjoy working here

Good employer

Learn more about Cedars Sinaiexternal

$96K - $164K/yr

Full-time

Posted 7 days ago

Job description


Dr. Andrew Hung is looking for a Research Data Scientist to join a diverse team!
The Research Data Scientist participates in biomedical research projects using programming, data mining, statistics, machine learning, and visualization techniques to lead the development, evaluation, and/or application of algorithms, methods, and software for data analysis. Responsibilities include querying databases, data processing, data cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and leading the communication of scientific findings via peer-reviewed publications and scientific conferences. Writes clean, performant, reusable code managed on GitHub to perform repeatable analyses and to train and deploy models to multiple environments.
Principal Responsibilities:
Leads the development, evaluation, and/or application of computational and statistical methods including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data.
Leads with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL, neo4j).
Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
Performs data cleaning, quality control, exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
Leads discussions with senior and/or lead research data scientists and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
Tests and validates code to ensure robustness of data applications with version control through GitHub.
Performs all other duties as assigned.
Qualifications
Education:
Bachelor's Degree, computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline - Required.
Master's Degree, computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline- Preferred
Work Experience:
2 years of professional experience in healthcare or pharmaceutical industries working with biomedical data - Required.
2 years of Experience programming at an intermediate skill level with a high-level programming language such as R or Python. College projects may be acceptable - Required.
2 years of Experience programming at a basic to intermediate proficiency level in SQL - Required.
No experience required Experience in biomedical machine learning is preferred

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