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Bioinformatics Machine Learning Jobs in California

ROSALIND

Bioinformatics Engineer

San Diego, CA · On-site

... machine learning algorithms for implementation within the ROSALIND multi-tenant SaaS platform • Be flexible and passionate about bioinformatics alchemy to support greater discovery into biology ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$140 - $190/hr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

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All JobsBioinformatics Machine Learning JobsBioinformatics Machine Learning Jobs in California

Bioinformatics Machine Learning information

See California salary details

$58.7K

$93.2K

$147.5K

How much do bioinformatics machine learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for bioinformatics machine learning in California is $93,237.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,600.00 and $127,800.00 per year, depending on experience, location, and employer.

What is a bioinformatics machine learning?

A Bioinformatics Machine Learning job involves applying machine learning techniques to analyze and interpret biological data, such as genomics, proteomics, and medical records. Professionals in this field develop algorithms, build predictive models, and enhance data-driven research in areas like personalized medicine and drug discovery. They work with large datasets, applying deep learning, neural networks, and other AI methods to extract meaningful insights. The role requires expertise in biology, statistics, and programming languages like Python or R.

What are the typical daily responsibilities for someone in a bioinformatics machine learning position?

In a Bioinformatics Machine Learning role, your daily tasks usually involve developing and tuning machine learning models to analyze large biological datasets, such as genomics or proteomics data. You'll collaborate closely with researchers, biologists, and data scientists to understand project goals, interpret results, and refine analytical approaches. Routine work includes coding, troubleshooting algorithms, visualizing data outputs, and documenting findings for internal teams or publication. The role often requires balancing independent analysis with teamwork and regular communication across disciplines, making it both technically challenging and highly collaborative.

What are the key skills and qualifications needed to thrive in the bioinformatics machine learning position, and why are they important?

A successful Bioinformatics Machine Learning professional needs a solid background in biology, statistics, and computer science, often backed by an advanced degree such as a Master's or PhD in bioinformatics, data science, or a related field. Proficiency with programming languages like Python or R, experience with machine learning libraries (e.g., TensorFlow, scikit-learn), and knowledge of version control systems are typical requirements, and relevant certifications can be beneficial. Strong problem-solving abilities, effective communication skills, and the capacity to work collaboratively in interdisciplinary teams set candidates apart. These skills are crucial for designing robust computational models, interpreting complex biological data, and translating findings into actionable insights in research or clinical settings.

Do bioinformatics machine learning professionals make a lot of money?

Bioinformatics machine learning professionals often earn competitive salaries due to the specialized skills in data analysis, programming, and biological sciences. Salaries vary based on experience, education, and location, but professionals in this field typically have higher earning potential compared to many other biotech roles. Advanced knowledge of tools like Python, R, and machine learning frameworks can also influence compensation levels.

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

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

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

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

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

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

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

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

Bioinformatics Machine Learning jobs near you
Infographic showing various Bioinformatics Machine Learning job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $93,237 per year, or $44.8 per hour.

Director, Machine Learning, Virtual Cell Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Re-posted 26 days ago

Job description

Job Summary:
Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. The Director of Machine Learning will lead the development of advanced machine learning models for the Virtual Cell Initiative, collaborating with multidisciplinary teams to innovate in the field of single-cell genomics.
Responsibilities:
• Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
• Work in an active learning loop with Arc’s wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
• Collaborate closely with other research groups to integrate genomics, functional track,and omics data more broadly beyond scRNA-seq data and Perturb-seq
• Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
• The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
• Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others.
• Attract the very best talent in the world to support VCI initiative goals
Qualifications:
Required:
• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
• Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
• Proven experience leading research teams in a fast paced, multi-disciplinary environment.
• Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
• Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.
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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