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Bioinformatics Machine Learning Jobs (NOW HIRING)

Jobtailor

Bioinformatics Scientist

California, MO · On-site

$120 - $180/hr

Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation ... D. or a Master's with 3+ years of industry experience in Bioinformatics, Computational Biology ...

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 ...

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How much do bioinformatics machine learning jobs pay per year?

As of Aug 29, 2026, the average yearly pay for bioinformatics machine learning in the United States is $94,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,500.00 and $129,500.00 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.
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Bioinformatics Machine Learning jobs near you
Infographic showing various Bioinformatics Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $94,474 per year, or $45.4 per hour.

Bioinformatics Scientist

Jobtailor

California, MO • On-site

$120 - $180/hr

Other

Posted 11 days ago

Job description

Professional Responsibilities
  • Develop, tune, and optimize novel assays, algorithms, machine learning and statistical models to analyze next-generation sequencing (NGS) and multimodal data for oncology biomarker detection from cell-free DNA
  • Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation and longitudinal treatment response monitoring
  • Improve molecular barcoding filtering strategies to distinguish low-frequency oncology biomarkers from sequencing artifacts
  • Design and integrate machine learning classifiers and filtering logic to differentiate Clonal Hematopoiesis variants from tumor-derived variants
  • Design and execute experiments evaluating assay analytical performance
  • Support regulatory documentation for CAP/CLIA, New York State, FDA, and MolDx submissions
  • Collaborate with wet-lab assay development scientists, medical directors, clinical scientists, biostatisticians, software engineers, and product managers
  • Translate research into clinically actionable insights and production-scale pipelines
Requirements
  • Must have completed a Ph.D. or a Master's with 3+ years of industry experience in Bioinformatics, Computational Biology, Cancer Biology, Genetics, Immunology, Molecular Biology, or Computer Science
  • In-depth knowledge of tools and pipelines for processing, aligning, and analyzing multimodal NGS data, including epigenetics, DNA, and RNA
  • Computational skills using Python and/or R, including data science and biological computing libraries
  • Expertise with AWS or GCP, Docker, and workflow management tools such as Nextflow or Snakemake
  • Scientific publications and/or contribution to successful industry product development
  • Strong background in statistical modeling, predictive/prognostic algorithms, and machine learning techniques
  • Effective communication and presentation skills
  • Self-driven and able to work well in interdisciplinary teams
Core Competencies

Demonstrates expertise in developing and optimizing machine learning models for analyzing next-generation sequencing data, with a strong focus on oncology biomarker detection and regulatory compliance. Proficient in translating complex research into actionable clinical insights and production-scale pipelines.

Highest-signal resume keywords
  • Ph.D. Or Master's In Bioinformatics
  • Machine Learning Model Development
  • Next-Generation Sequencing Data Analysis
  • Statistical Modeling And Predictive Algorithms
  • AWS Or GCP Expertise
ATS Optimization KeywordsHard Skills
  • Machine Learning
  • Statistical Modeling
  • Data Analysis
  • Bioinformatics
  • Computational Biology
  • Python
  • R
  • Molecular Biology
  • Cancer Biology
  • Genetics
Soft Skills
  • Effective Communication
  • Presentation Skills
  • Self-Driven
  • Team Collaboration
Industry Keywords
  • Oncology Biomarker Detection
  • Cell-Free DNA
  • Clonal Hematopoiesis
  • Regulatory Documentation
  • CAP/CLIA
  • FDA
  • MolDx
  • Multimodal Data
  • Assay Analytical Performance
  • Scientific Publications
Tools & Technologies
  • AWS
  • GCP
  • Docker
  • Nextflow
  • Snakemake
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