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Reinforcement Learning Jobs in Frisco, TX (NOW HIRING)

Research Scientist Senior

Grand Prairie, TX · On-site +1

$93K - $118K/yr

Develops scalable machine learning and reinforcement learning systems that improve healthcare outcomes, operational efficiency, and member experience through adaptive learning and advanced analytics.

Agentic AI Engineer Lead

Dallas, TX · On-site

$101K - $133K/yr

The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be ...

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Reinforcement Learning information

See Frisco, TX salary details

$26.7K

$54.6K

$74.9K

How much do reinforcement learning jobs pay per year?

As of Aug 25, 2026, the average yearly pay for reinforcement learning in Frisco, TX is $54,609.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,300.00 and $63,600.00 per year, depending on experience, location, and employer.

What is a reinforcement learning?

A Reinforcement Learning (RL) job involves designing, developing, and optimizing algorithms that enable machines to learn from interactions with their environment. RL professionals work on applications in robotics, finance, gaming, and autonomous systems, leveraging techniques like deep reinforcement learning and policy optimization. Responsibilities often include researching new models, implementing RL algorithms, and improving AI performance. Strong programming skills, knowledge of machine learning frameworks, and an understanding of mathematical concepts like probability and optimization are essential.

What does a reinforcement learning professional do?

A typical day for a Reinforcement Learning professional involves designing and implementing learning algorithms, running experiments, analyzing data, and iterating on models to improve performance. You might collaborate closely with data scientists, software engineers, and product managers to integrate your solutions into broader systems or products. Regular activities also include reading recent research literature and participating in team meetings to discuss progress and obstacles. This dynamic role often balances deep technical work with teamwork to drive innovative applications in areas such as robotics, recommendation systems, or autonomous systems.

What are the key skills and qualifications needed to thrive in the reinforcement learning position?

To thrive in a Reinforcement Learning role, you need a solid background in mathematics, statistics, machine learning, and programming (commonly with Python), typically supported by a relevant degree such as in computer science or engineering. Experience with frameworks like TensorFlow, PyTorch, OpenAI Gym, and familiarity with large-scale computing systems are highly valued. Strong problem-solving abilities, curiosity, and effective collaboration and communication skills help you excel in multidisciplinary research and project teams. These capabilities are crucial for designing, implementing, and refining complex algorithms that learn from interaction to solve real-world problems.

What can you do with reinforcement learning?

Reinforcement learning is used in roles such as reinforcement learning engineer or researcher to develop algorithms that enable systems to learn optimal actions through trial and error. It is applied in areas like robotics, game playing, autonomous vehicles, and recommendation systems, often requiring skills in programming, data analysis, and understanding of machine learning frameworks. Professionals in this field design, train, and evaluate models to improve decision-making processes in complex environments.

What are popular job titles related to Reinforcement Learning jobs in Frisco, TX?

For Reinforcement Learning jobs in Frisco, TX, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning jobs in Frisco, TX look for?

The top searched job categories for Reinforcement Learning jobs in Frisco, TX are:

What cities near Frisco, TX are hiring for Reinforcement Learning jobs?

Cities near Frisco, TX with the most Reinforcement Learning job openings:

Infographic showing various Reinforcement Learning job openings in Frisco, TX as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $54,609 per year, or $26.3 per hour.

Executive Director - Applied Artificial Intelligence Machine Learning

Plano, TX • On-site


JP Morgan Chase
Finance and Insurance • 10K+ employees

8.0

Company rating: 8.0 out of 10

Based on 497 frontline employees who took The Breakroom Quiz

71st of 172 rated banks

People enjoy working here

Good employer

Recommended by students


Full-time

Medical, Retirement

Re-posted 17 days ago


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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