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$55.4K

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How much do bioinformatics machine learning jobs pay per year?

As of Jun 7, 2026, the average yearly pay for bioinformatics machine learning in Texas is $88,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,900.00 and $120,600.00 per year, depending on experience, location, and employer.

What is a Bioinformatics Machine Learning job?

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.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Texas? The most popular types of Bioinformatics Machine Learning jobs in Texas are:
What are popular job titles related to Bioinformatics Machine Learning jobs in Texas? For Bioinformatics Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Machine Learning jobs in Texas look for? The top searched job categories for Bioinformatics Machine Learning jobs in Texas are:
Bioinformatics Machine Learning jobs near you
Infographic showing various Bioinformatics Machine Learning job openings in Texas as of May 2026, with employment types broken down into 98% Full Time, 1% Temporary, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $88,017 per year, or $42.3 per hour.
Sr. Bioinformatics ML/AI Engineer

Sr. Bioinformatics ML/AI Engineer

Baylor Miraca Genetics Laboratories, LLC

Houston, TX

Full-time

Posted 22 hours ago

Job description

A seasoned machine learning and AI application engineer with strong knowledge and hands-on experience in bioinformatics, genomic/clinical data modeling, AI/GenAI application development, data engineering, and cloud computing.

QUALIFICATIONS:

  • Education:
    • Master's or higher degree in Computer Engineering, Data Science, Bioinformatics, Machine Learning, and Data modeling, or related field with five (5) years of experience in genomic data analysis and application development.
  • Experience:
    • Hands-on experience in clinical bioinformatics pipeline development, including secondary/tertiary analysis, variant interpretation and classification pipeline R&D, and automated report generation
    • 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 (such as Huggingface, TensorFlow)
    • Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment.
    • Hands-on experience in RAG AI framework
    • Hands-on experience with scripting languages, such as Bash and Python
    • Strong experience in cloud platform (Azure) and data services (data lakehouse/data warehouse)
    • Experience in context-aware OCR
    • Experience in databases, including SQL and NoSQL
    • Familiarity with advanced data visualization techniques
    • 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

DUTIES AND RESPONSIBILITIES:

  • Serves as the SME in Bioinformatics ML/AI application development in a clinical genetic testing setting. Provides hands-on support towards building the company’s next-generation bioinformatics ML/AI platform
  • Designs, develops, evaluates, and deploys state-of-the-art ML/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 enhance the overall performance of the genetic testing workflow
  • Supports both internal and external data requirements by leveraging AI/ML 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

PHYSICAL DEMANDS AND WORK ENVIRONMENT:

  • Frequently required to sit
  • Frequently required to stand
  • Frequently required to utilize hand and finger dexterity
  • Frequently required to talk or hear
  • Frequently required to utilize visual acuity to operate equipment, read technical information, and/or use a keyboard
  • Occasionally exposed to bloodborne and airborne pathogens or infectious materials

EEO Statement:

Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.

Summary:

The Director, Corporate Financial Planning & Analysis is responsible for leading Baylor Genetics’ strategic financial planning, budgeting, forecasting, FP&A process improvement. This role plays a critical part in aligning financial strategy with long-term business goals. The Director will provide executive-level insights to leadership and external stakeholders while ensuring financial models and projections reflect the organization’s growth trajectory and performance.

Qualifications and Experience:
  • Education:
    • Bachelor's degree in Finance, Accounting, or a related field; MBA or relevant advanced degree preferred.
Experience:
  • Minimum of 10 years of experience in financial planning and analysis or corporate finance
  • At least 3 years in a financial leadership role
  • Proven success in FP&A process improvement, experience in Adaptive planning platform implementation required
  • Strong background in financial modeling, budgeting, and strategic forecasting
Duties and Responsibilities:
  • Strategic Financial Planning & Forecasting:
    • Lead the development of company-wide financial models and long-term forecasts
    • Translate strategic objectives into detailed financial plans aligned with organizational priorities
    • Collaborate with executive leadership to assess financial performance, risks, and growth opportunities
Budget and Forecast Management:
  • Oversee the annual budgeting process and rolling forecasts
  • Ensure alignment between actual results and forecasts, identifying key trends and drivers
  • Partner with department heads to develop financially sound operational plans
Revenue Analysis & Decision Support:
  • Lead revenue and margin analysis to support strategic decision-making
  • Drive business performance by analyzing sales trends, pricing strategies, and market dynamics
  • Provide financial insights that support resource allocation and investment decisions
Dashboards, Planning and Reporting:
  • Develop and maintain dashboards, planning and reporting tools for executive and departmental use including Adaptive planning platform
  • Provide timely and actionable financial insights to guide company performance
Team Leadership:
  • Build and lead a high-performing FP&A team
  • Foster a culture of collaboration, continuous improvement, and accountability
Physical Demands and Work Environment:
  • Frequently required to
  • Frequently required to utilize hand and finger
  • Frequently required to talk or
EEO Statement:

Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.

Note to Recruiters:

We value building direct relationships with our candidates and prefer to manage our hiring process internally. While we occasionally partner with select recruitment agencies for specialized roles, we do not accept unsolicited resumes from recruiters or agencies without a written agreement executed by the authorized signatory for Baylor Genetics ("Agreement"). Any resumes submitted to Baylor Genetics in the absence of an Agreement executed by Baylor Genetics' authorized signatory will be considered the property of Baylor Genetics, and Baylor Genetics will not be obligated to pay any associated recruitment fees.