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Reinforcement Learning Engineer Jobs in Houston, TX

The Friedkin Group

AI & Data Product Manager

Houston, TX · On-site

... reinforcement learning) and industry best practices into product strategy. * Backlog Management ... Drive collaboration across applied science, AI engineering, data engineering, software engineering ...

The Friedkin Group

AI & Data Product Manager

Houston, TX · On-site

... reinforcement learning) and industry best practices into product strategy. * Backlog Management ... Drive collaboration across applied science, AI engineering, data engineering, software engineering ...

The Friedkin Group

AI & Data Product Manager

Houston, TX · On-site

... reinforcement learning) and industry best practices into product strategy. * Backlog Management ... Drive collaboration across applied science, AI engineering, data engineering, software engineering ...

NAVA Software Solutions

Sr AI Agentic Engineer

Spring, TX · On-site

$93K - $127K/yr

This role works at the intersection of LLMs, systems engineering, and applied machine learning ... Apply reinforcement or feedback-driven optimization where applicable, including human-in-the-loop ...

NAVA Software Solutions

Senior AI Agentic Engineer

Spring, TX · On-site

$95K - $131K/yr

This role works at the intersection of LLMs, systems engineering, and applied machine learning ... Apply reinforcement or feedback-driven optimization where applicable, including human-in-the-loop ...

Nava Software Solutions

Senior AI Agentic Engineer

Spring, TX · On-site

$88K - $121K/yr

This role works at the intersection of LLMs, systems engineering, and applied machine learning ... Apply reinforcement or feedback-driven optimization where applicable, including human-in-the-loop ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Houston, TX

Reinforcement Learning Engineer information

See Houston, TX salary details

$36.3K

$110.6K

$182.9K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for reinforcement learning engineer in Houston, TX is $110,647.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,300.00 and $144,700.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

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

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

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

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

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

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

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 79% In-person, and 21% Remote job distribution, with an average salary of $110,647 per year, or $53.2 per hour.

Future 2 Learning Coach - MS

Houston Independent School District

Houston, TX • On-site

Full-time

Re-posted 4 days ago

Houston Independent School District rating

5.3

Company rating: 5.3 out of 10

Based on 32 frontline employees who took The Breakroom Quiz

545th of 639 rated elementary and secondary schools

Job description


JOB SUMMARY
The Future 2 Learning Coach plays a critical role in supporting student achievement and instructional execution within the Future 2 model. This position ensures smooth operations of the dyad learning environment while reinforcing student independence, Habits of Success, and engagement in both academic and experiential learning.
The Future 2 Learning Coach supports teachers in delivering high-quality instruction, managing mixed-grade cohorts, preparing learning environments, and reinforcing AI-enabled and adaptive learning systems. The Learning Coach helps maintain strong classroom culture, supports small-group instruction, and ensures students remain on track toward academic and experiential promotion requirements.
The Future 2 Learning Coach collaborates closely with teachers, teacher apprentices, administrators, and families to ensure students feel supported, accountable, and motivated in a structured yet innovative learning environment.
MAJOR DUTIES & RESPONSIBILITIES
1. Support implementation of high-quality core academic instruction aligned to HISD curriculum, accountability standards, and Future 2 design principles.
2. Prepare, organize, and maintain dyad learning spaces to ensure readiness for daily instruction and transitions.
3. Support smooth transitions between core instruction, adaptive learning blocks, team centers, and experiential learning activities.
4. Reinforce Habits of Success expectations and help maintain a structured, positive learning environment.
MAJOR DUTIES & RESPONSIBILITIES CONTINUED
5. Facilitate small-group reinforcement activities and monitor adaptive and AI-enabled learning platforms.
6. Support student independence during structured learning blocks and experiential preparation.
7. Assist teachers in monitoring, tracking, and organizing student progress data.
8. Provide supervision and instructional support during extended-day programming, experiential preparation, and field-based activities as assigned.
EDUCATION
Associate's degree or minimum of 60 college credit hours from an accredited college or university required.
Bachelor's degree preferred.
WORK EXPERIENCE
3-5 years of experience in an educational setting preferred.
Experience supporting instruction, mentoring students, or working in structured learning environments strongly preferred.
SKILL AND/OR REQUIRED LICENSING/CERTIFICATION
Strong organizational and time management skills.
Proficiency in Microsoft Office Suite
Ability to support instructional technology and adaptive learning systems.
Effective written and verbal communication skills.
Ability to work collaboratively in a fast-paced, non-traditional instructional model.
Strong interpersonal skills and ability to build rapport with students.
Demonstrated flexibility, problem-solving ability, and professionalism.
Commitment to confidentiality and ethical conduct.
LEADERSHIP RESPONSIBILITIES
No direct supervisory responsibilities. May provide guidance and modeling to students and support teacher apprentices as needed.
WORK COMPLEXITY/INDEPENDENT JUDGMENT
Work requires independent judgment in supporting instruction, managing transitions, and reinforcing student expectations. General supervision is provided with expectations for professionalism and responsiveness in a dynamic learning environment.
BUDGET AUTHORITY
None.
PROBLEM SOLVING
Position requires identifying student engagement challenges and supporting appropriate interventions in collaboration with teachers and administrators.
IMPACT OF DECISIONS
Position requires identifying student engagement challenges and supporting appropriate interventions in collaboration with teachers and administrators.
COMMUNICATION/INTERACTIONS
Regular interaction with students, teachers, apprentices, administrators, and families. Communication supports instructional alignment and student success.
CUSTOMER RELATIONSHIPS
Builds supportive relationships with students and families to reinforce accountability, growth, and positive school culture.
WORKING/ENVIRONMENTAL CONDITIONS
Work is performed in a school-based environment, including extended hours and occasional work outside the standard school day.
Ability to lift and/or carry less than 15 pounds.

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