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Health Machine Learning Jobs in Texas (NOW HIRING)

Bumble Inc.

Senior Machine Learning Engineer

Austin, TX · On-site

$220K - $250K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Introduction to the role & team At Bumble, we're building a world where all relationships are healthy and equitable, and machine learning is central to how we make that real for millions of people ...

Cotality

Principal Machine Learning Scientist

Dallas, TX · On-site

  • Medical

  • Life

  • Retirement

  • PTO

The Principal Machine Learning Scientist will design, develop, and deliver Machine Learning based ... Health: Multiple medical plan options with mental health and wellness support offerings.

Capital One

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other ...

ForeFlight

Staff Machine Learning Engineer

Austin, TX · On-site +1

$208K - $255K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Jeppesen ForeFlight is seeking a Senior Machine Learning Engineer to help build and scale domain ... Medical, dental, vision insurance with Employer paid health premiums * Open PTO Policy * 401(k) ...

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All JobsHealth Machine Learning JobsHealth Machine Learning Jobs in Texas

Health Machine Learning information

See Texas salary details

$23.8K

$39.7K

$82K

How much do health machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for health machine learning in Texas is $39,673.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What is health machine learning?

Health Machine Learning refers to the application of machine learning techniques and algorithms to healthcare data in order to improve medical decision-making, diagnostics, treatment plans, and patient outcomes. It involves using large amounts of health-related data, such as electronic health records, medical images, and genomic information, to train models that can predict diseases, assist in diagnosis, or personalize patient care. This field bridges computer science, data analytics, and medicine and is rapidly evolving to address complex healthcare challenges.

How do health machine learning professionals collaborate with clinical teams to implement AI solutions in healthcare settings?

Health Machine Learning professionals often work closely with clinicians, data scientists, and IT staff to develop and deploy AI-driven healthcare solutions. Collaboration involves understanding clinical workflows, validating models with real-world patient data, and ensuring that AI tools are both accurate and user-friendly. Regular meetings, cross-disciplinary workshops, and pilot project rollouts are common to ensure that the developed solutions address practical needs while complying with healthcare regulations. This teamwork is crucial for successful integration and adoption of machine learning models in clinical environments.

What are the key skills and qualifications needed to thrive as a health machine learning specialist?

To excel as a Health Machine Learning specialist, you need a strong background in computer science, statistics, and healthcare data, typically supported by degrees in relevant fields and proficiency in machine learning algorithms. Experience with programming languages like Python or R, frameworks such as TensorFlow or PyTorch, and knowledge of healthcare data standards (e.g., HL7, FHIR) are crucial, along with certifications like TensorFlow Developer or Data Science Professional. Strong problem-solving, attention to detail, and effective communication skills help you collaborate with clinicians and stakeholders to translate complex data into actionable insights. These skills ensure the development of accurate, ethical, and impactful machine learning solutions that improve healthcare outcomes.

What are popular job titles related to Health Machine Learning jobs in Texas?

For Health Machine Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Health Machine Learning jobs in Texas look for?

The top searched job categories for Health Machine Learning jobs in Texas are:

Health Machine Learning jobs near you
Infographic showing various Health Machine Learning job openings in Texas as of August 2026, with employment types broken down into 2% As Needed, 79% Full Time, 14% Part Time, and 5% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Executive Director - Applied Artificial Intelligence Machine Learning

JPMorgan Chase & Co

Plano, TX • On-site

Full-time

Medical, Retirement

Re-posted 10 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

72nd of 171 rated banks

Job description

As an Applied AI/ML Executive Director within our dynamic team, you will apply your quantitative, data science, and analytical skills to complex problems. As a Machine Learning Director, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. 
 

Job responsibilities

  • Develop advanced agentic AI solutions involving structured and unstructed data, casual analytics, machine learning, deep learning, reinforcement learning, and optimization.
  • Design robust agent architectures combining LLM reasoning with tools, structured data, and APIs spanning state, memory, and context management, plus loop engineering (plan/act/observe, verification, termination, and fallback/escalation).
  • Engineer reliable agent-driven workflows emphasizing correctness, traceability, and control-aware behavior (guardrails, approvals, auditable decision paths).
  • Build knowledge-centric reasoning layers, including knowledge graphs and hybrid retrieval (RAG + graph + structured sources) to improve grounding and accuracy.
  • Drive specification-driven development: author specs and contracts (schemas, validators, tool/skill interfaces) and build evaluation/regression harnesses.
  • Advance agent quality via recursive self-improvement through automated evaluation and critique loops, red-team feedback, skill/prompt instruction optimization, and outcome-driven dataset curation (human-in-the-loop as needed).
  • Coach and mentor AI/ML team members, setting a high bar for engineering rigor and research depth.
     

Required qualifications, capabilities, and skills

  • PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or with at least 5 years of industry experience or an MS with at least 7 years of industry or research experience in the field.
  • Extensive experience with machine learning and deep learning toolkits  (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
  • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
  • Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
  • Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments

  • Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities , and skills:

  • Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
  • Knowledge in search/ranking, Reinforcement Learning or Meta Learning
  • Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code
  • Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

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