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Reinforcement Learning Engineer Jobs in Texas (NOW HIRING)

Apptronik

Senior Autonomy Software Engineer

Austin, TX

$190K - $235K/yr

You will collaborate closely with Perception, Navigation, Controls, Reinforcement Learning, and ... Mentor junior engineers and provide technical leadership within the autonomy organization. Strong ...

Apptronik

Software Engineer - Human Motion Data

Austin, TX

$113K - $136K/yr

JOB SUMMARY As a Software Engineer- Human Motion Data, you will leverage your background in robotics to build the crucial link between human-data and our reinforcement learning pipelines. This role ...

Synthesia

Software Engineer - Human Motion Data

Austin, TX

$113K - $136K/yr

JOB SUMMARY As a Software Engineer- Human Motion Data, you will leverage your background in robotics to build the crucial link between human-data and our reinforcement learning pipelines. This role ...

Apptronik

Software Engineer - Human Motion Data

Austin, TX · On-site

$113K - $136K/yr

JOB SUMMARY As a Software Engineer- Human Motion Data, you will leverage your background in robotics to build the crucial link between human-data and our reinforcement learning pipelines. This role ...

IT America Inc

Agentic AI Engineer Lead

Dallas, TX · On-site

$101K - $133K/yr

Agentic AI Engineer Lead Location: Dallas, TX & Basking ridge, NJ - Day one Onsite ( 5 days ... Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved ...

Adidev Technologies Inc

ML/AI Engineers

Austin, TX · On-site

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... reinforcement learning, and/or other AI domains. · Demonstrable experience with Generative AI ...

Adidev Technologies Inc

ML/AI Engineers

Austin, TX · On-site

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... vision, reinforcement learning, and/or other AI domains. • Demonstrable experience with ...

Tata Consultancy Service Limited

AI Developer

Mckinney, TX · On-site

$100K - $130K/yr

Neural Networks, Decision Trees, SVM, NLP, Reinforcement Learning, Ensemble Methods, MCP • Strong knowledge with RAG (Retrieval-Augmented Generation), Prompt Engineering, Agentic AI • Knowledge ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Texas

Reinforcement Learning Engineer information

See Texas salary details

$35.4K

$107.9K

$178.4K

How much do reinforcement learning engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for reinforcement learning engineer in Texas is $107,946.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,300.00 and $141,100.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

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 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 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 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 Texas? For Reinforcement Learning Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Texas look for? The top searched job categories for Reinforcement Learning Engineer jobs in Texas are:
What cities in Texas are hiring for Reinforcement Learning Engineer jobs? Cities in Texas with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Texas as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $107,946 per year, or $51.9 per hour.
AI / Machine Learning Engineer Staff (Electronic Warfare)

AI / Machine Learning Engineer Staff (Electronic Warfare)

Lockheed Martin

Fort Worth, TX • On-site, Remote

Full-time

Posted 8 days ago

Lockheed Martin rating

8.2

Company rating: 8.2 out of 10

Based on 382 frontline employees who took The Breakroom Quiz

31st of 60 rated aerospace companies

Job description

Job Description:

We are seeking a highly motivated and experienced Artificial Intelligence Engineer to join our Lockheed Martin Artificial Intelligence Center (LAIC) team. As a key member of our Applied AI team, you will play a critical role in developing technologies and products that leverage Artificial Intelligence to provide discriminating signal processing capabilities to our customers. You will work on a broad range of projects across the LAIC, from low Technical Readiness Level research to deployment and will be responsible for leading critical technical projects.
Key Responsibilities:
• Develop and Apply AI Technologies
• Develop and apply current AI paradigms, including computer vision, deep learning, and reinforcement learning, to solve complex signal processing problems and field innovative solutions.
• Engage in every phase of the system development lifecycle, including requirements generation, system and software design, implementation, integration, and flight test.
• Take ownership of critical tasks and lead technical teams to deliver high-quality solutions.
• Participate in the development of proposals and whitepapers to secure funding for AI research and development projects
Technical Leadership and Mentorship:
• Assume technical lead responsibilities and mentor junior engineers to help them develop their skills and expertise.
• Provide guidance and support to team members to ensure successful project execution.
• Collaboration and Communication:
• Work collaboratively with cross-functional teams to develop and deploy AI solutions.
• Communicate complex technical concepts and solutions to non-technical stakeholders.
• Engage with other Lockheed Martin teams to identify opportunities for AI adoption and application.
Technical Skills:
• Strong background in software engineering, artificial intelligence, and machine learning.
• Strong background in signal processing theory and application (radar, communication, electronic warfare, sonar, audio, or biomedical)
• Experience with current AI paradigms, including computer vision, deep learning, and reinforcement learning.
• Proficiency in programming languages such as Python, Java, or C++.
Soft Skills:
• Self-motivation, strong work ethic, and time management skills.
• Excellent interpersonal and communication skills.
• Engage with other Lockheed Martin teams to identify opportunities for AI adoption and application
• Education and Experience:
• Bachelor's degree in a relevant field, such as computer science, electrical engineering, or mathematics.
• 5+ years of experience in AI or a related field.
What We Offer:
• Opportunity to Work on High-Impact Projects:
• Work on a broad range of projects across the LAIC, from low TRL research to deployment.
• Develop and apply AI technologies to solve complex problems and field innovative solutions.
• Collaborative and Dynamic Work Environment:
• Work collaboratively with cross-functional teams to develop and deploy AI solutions.
• Participate in a fast-paced and dynamic work environment with a focus on innovation and experimentation.
• Professional Development and Growth Opportunities:
• Opportunities for professional growth and development in AI and related fields.
• Mentorship and guidance from experienced engineers and leaders.
The preferred work locations for this position are Lockheed Martin facilities in Fort Worth, TX, or Palmdale, CA. Remote work arrangements may also be considered for qualified candidates.
#LMLAIC

Qualifications:

• Bachelor’s Degree in Engineering, Computer Science, or other related discipline
• Experience developing with machine learning frameworks (Pytorch, Tensorflow, JAX, Keras, etc.)
• Experience with Python and multiple libraries (NumPy, OpenCV, Scikit, Pandas, SciPy, etc.)
• Experience with machine learning and deep learning for signal processing applications such as radar, communication, electronic warfare, sonar, audio, or biomedical

What Lockheed Martin employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Lockheed Martin

Sourced by ZipRecruiter

As a global security and aerospace company, the majority of Lockheed Martin's business is with the U.S. Department of Defense and U.S. federal government agencies.The remaining portion of Lockheed Martin's business is comprised of international government and commercial sales of products, services and platforms.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Bethesda, MD, US

Year founded

1912

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