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Bioinformatics Machine Learning Jobs (NOW HIRING)

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 ...

Axle

Bioinformatics Engineer

Rockville, MD · On-site

They are seeking a Bioinformatics Engineer to join their team supporting major pharmaceutical ... machine learning applications • Implement best practices for workflow versioning ...

GATC Health

Bioinformatics Analyst - CA

Irvine, CA · On-site

Preferred : • Experience using or interfacing with machine learning algorithms. • Experience ... and bioinformatics innovation. Company : GATC Health uses AI to speed drug discovery, predict ...

Bruker

The Bioinformatician will furthermore play a role in performing CellScape data analyses for key ... Hands-on experience developing machine-learning or deep-learning models (training, evaluation, and ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site

$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 ...

UNAVAILABLE

Scientist, Bioinformatics

Saint Louis, MO · On-site

The Bioinformatician will furthermore play a role in performing CellScape data analyses for key ... Hands-on experience developing machine-learning or deep-learning models (training, evaluation, and ...

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Bioinformatics Machine Learning information

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How much do bioinformatics machine learning jobs pay per year?

As of Aug 9, 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.

More about Bioinformatics Machine Learning jobs
What cities are hiring for Bioinformatics Machine Learning jobs? Cities with the most Bioinformatics Machine Learning job openings:
What are the most commonly searched types of Bioinformatics Machine Learning jobs? The most popular types of Bioinformatics Machine Learning jobs are:
What states have the most Bioinformatics Machine Learning jobs? States with the most job openings for Bioinformatics Machine Learning jobs include:
What job categories do people searching Bioinformatics Machine Learning jobs look for? The top searched job categories for Bioinformatics Machine Learning jobs are:
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, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $94,474 per year, or $45.4 per hour.

Senior Scientist, Bioinformatics

Kenai Therapeutics

San Diego, CA • On-site

$140K - $155K/yr

Full-time

Re-posted 8 days ago

Job description

Kenai Therapeutics is seeking a skilled and versatile computational biologist to join our highly collaborative, multidisciplinary, and dynamic team advancing next-generation allogeneic cell therapies for neurological diseases. As Senior Scientist of Bioinformatics, the ideal candidate will drive computational analysis and pipeline development across CMC and research programs. This candidate brings scientific rigor, deep hands-on expertise in single-cell and multiomics analysis, and a strong foundation in statistics and machine learning to generate actionable insights that inform therapeutic decision-making. This role requires exceptional technical skills, a proven ability to communicate complex findings across scientific disciplines, and a desire to thrive in a small, fast-moving organization where flexibility and initiative are essential.
Key Responsibilities:
  • Design, implement, and maintain scalable, reproducible pipelines for single-cell RNA-seq, spatial transcriptomics, and integrative multiomics data analysis, from raw data through biological interpretation
  • Apply statistical modeling and machine learning approaches to large-scale omics datasets to identify biomarkers, characterize cellular heterogeneity, and aid process development
  • Leverage AI-based tools and platforms to accelerate research workflows, automate analyses, and enhance software development productivity
  • Perform complex data interpretation across modalities (scRNA-seq, genomics, spatial omics, proteomics) and translate findings into actionable insights for programs and leadership
  • Partner closely with manufacturing and research teams to align computational efforts with therapeutic objectives and program priorities
  • Contribute to data infrastructure strategy, supporting robust systems for data storage, integration, traceability, and long-term analytics
  • Communicate results effectively through internal presentations, and cross-functional meetings; distill complex analyses into clear narratives for diverse audiences.

Requirements
  • Ph.D. in bioinformatics, computational biology, genomics, statistics, or a related quantitative discipline with 3+ years of relevant industry experience
  • Self-motivated, hardworking, and adaptable
  • Strong foundation in statistics and machine learning, including supervised and unsupervised methods, dimensionality reduction, and model evaluation
  • Deep hands-on experience with single-cell analysis frameworks (e.g., Scanpy, Seurat, scVI) and associated workflows across the full analytical lifecycle
  • Strong proficiency in Python and R for data analysis, visualization, and pipeline development; Javascript experience is a plus
  • Demonstrated experience supporting drug discovery and development programs with computational and bioinformatic analyses
  • Proficiency in utilizing AI and large language model-based tools for research acceleration and software development
  • Excellent written and verbal communication skills, including the ability to present complex technical work to both computational and non-computational audiences
  • Strong team player with a collaborative mindset and a commitment to working in a small, tight-knit, and high-performing team environment

Preferred
  • Background in neuroscience, developmental biology, or related areas of disease biology
  • Experience in cell therapy research, manufacturing analytics, or related cell-based therapeutic modalities
  • Familiarity with spatial transcriptomics platforms (e.g., 10x Visium, Xenium, MERFISH) and integrative multiomics approaches
  • Track record of scientific contributions evidenced by peer-reviewed publications, patents, or conference presentations

Benefits
Kenai Therapeutics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
The salary range for this position is $140,000 USD to $155,000 USD annually. This salary range is an estimate, and the actual salary may vary based on experience and/or the Company's compensation practices.

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