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Bioinformatics Machine Learning Jobs (NOW HIRING)

Baylor Genetics

Lead Bioinformatics AI Scientist

Education: * Master's or higher degree (PhD preferred) in Bioinformatics, Machine Learning and AI, Computer Science, Data Science or related quantitative field. * Experience: * 8+ years of ...

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 ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

Baylor Genetics

Lead Bioinformatics Scientist

Scientific and Technical Leadership: o Serve as a scientific authority in bioinformatics, computational biology, statistical, and machine learning methods for genomic and clinical data analysis. o ...

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How much do bioinformatics machine learning jobs pay per year?

As of Aug 8, 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.

Lead Bioinformatics AI Scientist

Baylor Genetics

Remote

Full-time

Re-posted 7 days ago

Baylor Genetics rating

8.4

Company rating: 8.4 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

27th of 120 rated laboratories

Job description

Baylor Genetics is seeking an accomplished and visionary Lead Bioinformatics AI Scientist to advance innovation within the Bioinformatics R&D and Data Science organization. This individual will serve as a scientific and technical leader, driving the design, development, and implementation of advanced AI methods, algorithms, and workflows to enhance Baylor Genetics' clinical testing and genomic data analysis capabilities.
The Lead Bioinformatics AI Scientist will play a central role in AI-powered genomics research and data analysis, focusing on identifying novel AI solutions, training and fine-tuning GenAI models, developing AI applications, and more. The successful candidate will combine deep scientific expertise in genomics, bioinformatics, and AI modeling with strong technical skills in AI/ML algorithm design and data analysis, developing next-generation AI-empowered platforms for clinical-grade genomic analysis.
QUALIFICATIONS:
  • Education:
    • Master's or higher degree (PhD preferred) in Bioinformatics, Machine Learning and AI, Computer Science, Data Science or related quantitative field.
  • Experience:
    • 8+ years of professional experience in bioinformatics, AI application development, machine learning and/or genomic data analysis, including 3-5 years in a principal or leadership role.
    • Hands-on experience in state-of-the-art GenAI application development, LLM model turning, agentic AI, and model context protocol (MCP).
    • Hands-on experience in building and/or adopting novel AI and GenAI solutions for business specific applications, especially in the field of clinical testing and genomic data analysis.
    • Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment in the production environment requiring fast turn-around-time (TAT) and high reliability.
    • Hands-on experience in human genetics/multi-omics data modeling and application development especially in next-generation sequencing data.
    • Hands-on experience in machine learning framework (Huggingface, TensorFlow, PyTorch, etc.).
    • Hands-on experience with scripting language, such as Bash and Python.
    • Strong experience in cloud platform (Azure, AWS, GCP) and data services (data lakehouse/data warehouse).
    • Experience in context-aware OCR.
    • Experience in databases, including SQL and no-SQL.
    • DevOps experience such as unit testing, CI/CD is a plus.
    • Strong curiosity and the ability to learn quickly and adapt to a fast-changing environment.
  • Core Competencies:
    • Strong scientific reasoning and analytical problem-solving skills.
    • Proven ability to lead R&D initiatives from concept through validation and deployment.
    • Deep understanding of genomic data, AI applications, and biological context.
    • Excellent written and verbal communication for technical and clinical translation.
    • Collaborative mindset and ability to work across disciplines.
    • Commitment to innovation, quality, and patient-centered outcomes.

DUTIES AND RESPONSIBILITIES:
  • Serves as the visionary leader in Bioinformatics AI application development in a clinical genetic testing setting. Provides technical guidance and hands-on support towards building company's next-generation bioinformatics AI platform.
  • Identifies, prototypes, and develops state-of-the-art AI applications to revolutionize clinical testing and genomic analysis workflow.
  • Designs, develops, evaluates, and deploys novel AI solutions to gain valuable data insights based on the genetical, phenotypical, and clinical datasets.
  • Evaluates, adopts, and customizes GenAI models based on both internal and external datasets to build next-generation clinical genetic testing platforms.
  • Supports both internal and external data requirements by leveraging AI and GenAI capabilities to keep up with the increasing demands of the business.
  • Collaborates in a multidisciplinary and regulated clinical diagnostics environment with geneticists, bioinformaticians, software engineers, and IT infrastructure professionals

WHY JOIN BAYLOR GENETICS
At Baylor Genetics, you'll join a world-class team dedicated to transforming clinical genomics through scientific excellence and technological innovation. As a Lead Bioinformatics AI Scientist, you'll have the opportunity to drive the development of new AI- and GenAI-empowered approaches that redefine clinical testing, genomics data analysis, and precision diagnostics.
You will collaborate with leading scientists, engineers, and clinicians to deliver discoveries that matter, advancing the frontiers of precision medicine and improving lives through genomic insight.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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