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Bioinformatics Machine Learning Jobs in California

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

Tempus AI, Inc.

Bioinformatics Scientist

Redwood City, CA · On-site

$100 - $175/hr

We are seeking a highly motivated and capable Bioinformatics Scientist to join our Liquid Biopsy ... Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation ...

Tempus

Bioinformatics Scientist

Redwood City, CA · On-site

We are seeking a highly motivated and capable Bioinformatics Scientist to join our Liquid Biopsy ... Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation ...

Tempus

Bioinformatics Scientist

Redwood City, CA · On-site +1

We are seeking a highly motivated and capable Bioinformatics Scientist to join our Liquid Biopsy ... Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation ...

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Showing results 21-40

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 22, 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.

Senior Bioinformatics Scientist

CEDENT

South San Francisco, CA

Full-time

Re-posted 4 hours ago

Job description

We are seeking a highly motivated and innovative Senior/Staff Bioinformatics Scientist to join our R&D team focused on synthetic biology product development. In this role, you will work at the intersection of computational and molecular biology, developing advanced DNA sequence analysis pipelines, gene design algorithms, and predictive models to optimize DNA synthesis and assembly.
You will collaborate with molecular biologists, product teams, and manufacturing engineers to refine client’s core synthetic biology platform, troubleshoot assembly challenges, and improve DNA synthesis efficiency. This position emphasizes predictive modeling, algorithm development, and data-driven approaches to enhance synthetic biology workflows.
Key Responsibilities
Synthetic Biology & DNA Assembly
  • Develop bioinformatics methods supporting DNA assembly strategies and synthetic biology workflows.
  • Apply machine learning and predictive modeling to improve DNA assembly success rates and optimize synthesis parameters.
  • Collaborate with wet-lab scientists to analyze and troubleshoot molecular biology processes.
  • Develop bioinformatics approaches for diagnosing and resolving complex DNA synthesis and assembly issues.
NGS Pipeline Development & Data Science
  • Build and maintain NGS analysis pipelines (e.g., Nextflow) to support quality control and performance tracking of synthetic biology products.
  • Leverage Oxford Nanopore Technologies (ONT), Illumina, or PacBio sequencing to analyze and optimize synthesis workflows.
  • Develop predictive models to identify challenging sequences and recommend optimizations to improve synthesis efficiency.
  • Ensure pipeline accuracy, reproducibility, and scalability in research environments.
Data Analysis & Insights
  • Apply advanced statistical and machine learning methods to evaluate improvements in synthetic biology product iterations.
  • Use Python, R, and visualization tools to generate actionable insights and present findings to stakeholders.
  • Design and implement novel bioinformatics algorithms for sequence analysis and synthetic biology applications.
Cross-Functional Collaboration
  • Partner with R&D, manufacturing, and product development teams to troubleshoot assay issues and implement data-driven solutions.
  • Support the broader Bioinformatics team by integrating synthetic biology workflows with existing genomic data processing pipelines.
  • Assist with customer-facing analyses related to synthetic biology assay performance.
Required Qualifications
  • Educational Background & Experience:
  • Bachelor’s/Master’s degree with 6–8 years of industry experience, or a Ph.D. with 3+ years of industry experience in Bioinformatics, Molecular Biology, Biochemistry, Genetics, Genomics, Computational Biology, or a related field.
  • Bioinformatics & NGS Expertise:
  • Experience with ONT, Illumina, or PacBio sequencing technologies.
  • Proficiency in workflow management tools (Nextflow, Snakemake).
  • Hands-on experience designing predictive models for sequence design & synthetic biology applications.
  • Technical Skills:
  • Expertise in Python (Pandas, NumPy, SciPy) and visualization libraries (Matplotlib, Seaborn, Plotly).
  • Experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch) applied to biological sequence data.
  • Familiarity with R, SQL, or other statistical tools.
  • Molecular Biology & Synthetic Biology Knowledge:
  • Understanding of DNA assembly, cloning techniques, and molecular biology workflows.
  • Ability to interpret experimental data and provide feedback on laboratory procedures.
Preferred Qualifications
  • Experience developing design algorithms for synthetic biology applications.
  • Familiarity with deep learning approaches for biological sequence analysis.
  • Exposure to high-throughput experimental design and laboratory automation.
  • Hands-on experience with gene synthesis and synthetic biology assay development.
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About Cedent

Sourced by ZipRecruiter

CEDENT strives to attract and retain the best people and provide an environment where they can all develop professionally and build a rewarding career. As a result, we create an inclusive environment that is rich in diversity, acknowledges each individual's uniqueness and promotes respect, personal achievement and stewardship. Our clients are global and so is CEDENT. We build and maintain a global workforce that includes people from different backgrounds, with a vast range of skills and experience all united by a common culture and commitment to help our clients achieve high performance. Cultivating a diverse workforce and inclusive work environment makes business sense. Our peoples varied skills are the talent engine that powers CEDENT, enabling it in turn to deliver the innovative solutions that help our clients outperform competitors.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

Plano, TX, US

Year founded

2008

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