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Bioinformatics Machine Learning Jobs in California

Experience using or interfacing with machine learning algorithms. * Experience analyzing and ... Computational biology and bioinformatics innovation. Why Join Us: • Opportunity to work at the ...

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning ... Experience in NGS data analysis and bioinformatic pipelines. * Experience with containerized cloud ...

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into ... Previous experience in data extraction and curation from bioinformatics data sources * Familiarity ...

Ph.D. in bioinformatics, computational biology, genetics, or computer science. * 2 or more years of experience with machine learning or AI applications in biology. * 2 or more years of experience ...

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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 Jun 8, 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 job?

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.

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 cities in California are hiring for Bioinformatics Machine Learning jobs? Cities in California with the most Bioinformatics Machine Learning job openings:
Infographic showing various Bioinformatics Machine Learning job openings in California as of May 2026, with employment types broken down into 98% Full Time, 1% Temporary, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $93,237 per year, or $44.8 per hour.
Bioinformatics Analyst - CA

Bioinformatics Analyst - CA

GATC Health

Irvine, CA

Full-time

Posted 25 days ago


Job description

Company Overview: GATC Health is an innovative TechBio company at the forefront of revolutionizing pharmaceutical discovery and accelerating their development through the integration of artificial intelligence (AI), science and finance. Our company is dedicated to advancing therapeutic discoveries and improving human health by leveraging the power of technology and interdisciplinary collaboration.
 
Position Overview: We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines for primary, secondary, and tertiary analysis of data generated from transcriptional, proteomic, and mult-omic assays. As a Bioinformatics Scientist, you will innovate, develop and implement novel analysis methods for different data types from sparse to large and complex datasets to support the internal development and validation of new pharmaceutical assets and the development of end-user, customer-facing data analysis and visualization for biotech customers and stakeholders. A highly motivated scientist with broad expertise and experience in bioinformatics, computational biology, transcriptomics, proteomics and multi-omics would be an ideal fit for this position.
 
Roles and Responsibilities
  • Prep and Process data through GATC platform based on customer or internal end user requirements.
  • Implement primary and secondary analysis tools for GATC’s assays.
  • Work with cross-disciplinary R&D teams to develop and implement new discovery and risk assessment product applications.
  • Aid in Development and implementation processes and algorithms for multi-modal datasets, scalable to very large numbers of samples.
  • Engage with external collaborators on the evaluation of beta version products and analysis of novel data.
Role Requirements
  • Degree in computational biology, bioinformatics, computer science or similar.
  • Experience analyzing complex multi-omic datasets, including human or single cell data.
  • Experience implementing, and evaluating novel bioinformatics algorithms and pipelines.
  • Experience in programming in scripting (Python or similar) and interpreted languages (R, etc).
  • Demonstrated ability to become proficient in new fields and work with interdisciplinary teams.
  • Excellent verbal/written communication and interpersonal skills with scientist and non-scientists.
Role Preferences
  • Experience using or interfacing with machine learning algorithms.
  • Experience analyzing and interpreting large-scale human or single cell datasets.
  • Experience with professional software development methods and tools in a team environment.
  • Experience in programming in scripting (Python), interpreted (R ) and compiled languages (C++ / Rust / Java).
  • Experience working with collaborators, including lab scientists on multi-omic method development.
  • Experience visualizing scientific datasets and results.
  • Experience using cloud computing environments.
  • Computational biology and bioinformatics innovation.
Why Join Us:
• Opportunity to work at the intersection of technology and science, driving innovation in pharmaceutical discovery.
• Collaborative and inclusive work culture that values diversity, creativity, and continuous learning.
• Competitive compensation package, including salary, benefits, and opportunities for professional development.
• Chance to make a meaningful impact on human health and contribute to groundbreaking research and development projects.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.