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Bioinformatics Machine Learning Jobs in California

Bioinformatics Scientist

Redwood City, CA · On-site

$115K - $175K/yr

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 ...

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 ...

Develop, train, and evaluate machine learning models, driving algorithm design decisions that ... D. in Bioinformatics, Computer Science, Engineering, Biochemistry, or a related field, with a ...

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 ...

Showing results 41-60

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 Sep 14, 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:

Infographic showing various Bioinformatics Machine Learning job openings in California as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $93,237 per year, or $44.8 per hour.

Bioinformatics Scientist

Redwood City, CA • On-site

$115K - $175K/yr

Other

Posted 27 days ago


Tempus AI rating

7.7

Company rating: 7.7 out of 10

Based on 9 frontline employees who took The Breakroom Quiz


Job description

Passionate about precision medicine and advancing the healthcare industry? Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way.

Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

We are seeking a highly motivated and capable Bioinformatics Scientist to join our Liquid Biopsy Science team. This role will focus directly on assay and algorithmic development, optimization, and analytical validation of our next-generation Liquid Biopsy assays. The ideal candidate will possess deep technical and biological expertise to address key liquid biopsy challenges for various applications including diagnostics, complete genomic profiling, therapeutic selection, and treatment response monitoring (TRM).

Core Duties and Responsibilities
  • High-Sensitivity Biomarker Detection: Develop, tune, and optimize novel assays, algorithms, machine learning and statistical models to analyze next-generation sequencing (NGS) and multimodal data to detect oncology related biomarkers (SNV/indel/CNV/rearrangements, MSI, bTMB) from cell free DNA.
  • Tumor Fraction Estimation & Modeling: Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation and tracking, enabling robust evaluation for longitudinal treatment response monitoring (TRM).
  • Noise Suppression & Error Correction: Improve advanced molecular barcoding filtering strategies to distinguish true low-frequency oncology-related biomarkers from background sequencing artifacts.
  • Clonal Hematopoiesis (CHIP) Disambiguation: Design and integrate machine learning classifiers and filtering logic to effectively differentiate non-tumor-derived Clonal Hematopoiesis variants from true tumor-derived variants, protecting patients from inappropriate therapy selections.
  • Performance Characterization & Regulatory Support: Design and execute experiments to evaluate the assay’s analytical performance to support regulatory documentation for CAP/CLIA, New York State (NYS), FDA, and MolDx submissions.
  • Cross-Functional Collaboration: Work closely with wet-lab assay development scientists, medical directors, clinical scientists, biostatisticians, software engineers, and product managers to translate cutting-edge research into clinically actionable insights and production-scale pipelines.
Qualifications and Competencies
  • Must have completed a Ph.D. or a Masters with 3+ years of industry experience in Bioinformatics, Computational Biology, Cancer Biology, Genetics, Immunology, Molecular Biology, or Computer Science
  • In-depth knowledge of modern tools and pipelines for processing, aligning, and analyzing multimodal NGS data (including epigenetics, DNA, RNA).
  • Computational skills using Python and/or R, including experience with data science and biological computing libraries.
  • Expertise with cloud computing environments (AWS or GCP), container solutions (Docker), and common workflow management tools (Nextflow, Snakemake)
  • Proven scientific reputation as demonstrated by scientific publication and/or contribution to successful product development in industry
  • Strong background in constructing statistical models, creating predictive/prognostic algorithms, and applying machine learning techniques.
  • Demonstrated effective communication and presentation skills
  • Self-driven and works well in interdisciplinary teams

CHI: $100,000-$160,000 USD SF: $115,000-$175,000 USD The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience.

Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.

Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote roles- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Tempus was founded in August of 2015 by Eric Lefkofsky, after his wife was diagnosed with Breast Cancer. Shortly after he founded the company in an effort to bring the power of technology and artificial intelligence to cancer care, he convinced Ryan Fukushima to join as the company’s first employee. Ryan and Eric began assembling a world class team, focused on building the first version of a platform capable of ingesting real time healthcare data in an effort to personalize diagnostics. We built the platform for oncology and have expanded it to neuropsychiatry, cardiology, infectious disease (through COVID), and radiology. Despite our rapid growth, our mission remains the same—to help make sure patients are on the right drug at the right time, so they can live longer and healthier lives.

We're looking for people who can change the world. Who question the status quo and don't shy away from tough problems. For the builders who are never done building and the learners who are never done learning. We're looking for passionate people with undying curiosity. Those who want to attack one of the most challenging problems mankind has ever faced. Head on.

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