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Sim Racing Jobs in Texas (NOW HIRING)

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls ... race, color, religion, age, sex, national origin, disability status, genetics, protected veteran ...

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$10.2K

$120.8K

$184.5K

How much do sim racing jobs pay per year?

As of Jun 4, 2026, the average yearly pay for sim racing in Texas is $120,804.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $129,000.00 per year, depending on experience, location, and employer.

What is a Sim Racing job?

A Sim Racing job involves working in the competitive or professional side of simulated motorsports, which can include roles such as esports driver, coach, content creator, engineer, or software developer. Sim racers may compete in online leagues, represent teams or brands, and even collaborate with real-world racing teams for driver training. Other roles involve setting up simulator hardware, developing racing software, or broadcasting and analyzing esports events.

What are the key skills and qualifications needed to thrive in the Sim Racing position, and why are they important?

To excel in Sim Racing, strong hand-eye coordination, quick reflexes, and a deep understanding of racing lines and vehicle dynamics are essential, often developed through extensive practice and participation in competitive leagues. Familiarity with industry-standard racing simulators, high-end sim rig setups, and telemetry analysis software is highly valued. Effective communication, discipline, and adaptability set top performers apart, especially in team-based or league settings. These competencies are crucial for consistent performance, progressing in competitions, and collaborating with teams or sponsors.

What does a typical workweek look like for someone in a Sim Racing role?

A typical workweek for a Sim Racing professional usually involves a mix of solo practice, team strategy sessions, race events, and content creation or community engagement. Time is spent honing driving skills, analyzing data to fine-tune performance, and coordinating with engineers or teammates for upcoming races. Professionals often participate in both live-streamed events and offline leagues, requiring flexibility to accommodate irregular race schedules. Collaboration and communication with coaches, sponsors, and other racers also play key roles in a successful and dynamic workweek.
More about Sim Racing jobs
What are the most commonly searched types of Sim Racing jobs in Texas? The most popular types of Sim Racing jobs in Texas are:
What are popular job titles related to Sim Racing jobs in Texas? For Sim Racing jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Sim Racing jobs in Texas look for? The top searched job categories for Sim Racing jobs in Texas are:
What cities in Texas are hiring for Sim Racing jobs? Cities in Texas with the most Sim Racing job openings:
Sim Racing jobs near you
Infographic showing various Sim Racing job openings in Texas as of May 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 100% In-person job distribution, with an average salary of $120,804 per year, or $58.1 per hour.
Senior Reinforcement Learning Engineer

Senior Reinforcement Learning Engineer

Apptronik

Austin, TX • On-site

$103K - $142K/yr

Full-time

Posted 8 days ago

Job description

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond.
We operate at the cutting edge of embodied AI, applying our expertise across the full robotics stack to solve some of society's most important problems. You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.
JOB SUMMARY
The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots. This engineer will leverage their deep expertise in RL to solve critical locomotion and manipulation challenges and deliver breakthrough results on physical hardware. The primary focus of this role is to rapidly implement, iterate, and deploy advanced learning algorithms to push the boundaries of what our robots can do. As a senior member of the team, this individual will also be responsible for mentoring junior engineers, elevating the team's overall technical capabilities through their guidance and expertise.
ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES
  • Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
  • Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot.
  • Optimize and scale the RL training pipeline for faster iteration, contributing to core infrastructure for high-throughput simulation and distributed training.
  • Mentor junior engineers by providing technical guidance, conducting insightful code reviews, and sharing best practices in reinforcement learning and software development.
  • Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co-develop solutions that enable more complex learned behaviors.
  • Analyze and present hardware results to guide future technical directions and demonstrate progress on key company objectives.
  • Develop and refine motion retargeting pipelines to translate human demonstration data (mocap, teleoperation) into robust reference trajectories for reinforcement learning.

SKILLS AND REQUIREMENTS
  • Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX) and high-fidelity physics simulators (e.g., MuJoCo, IsaacGym)
  • Mastery of Python for rapid prototyping and training, alongside strong proficiency in C++ for developing performant, deployable code.
  • Experience building or utilizing large-scale, distributed training pipelines and a strong intuition for their optimization.
  • A strong theoretical understanding of modern reinforcement learning, including deep expertise in areas like imitation learning, model-based RL, and sim-to-real transfer techniques.
  • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches.
  • A results-oriented mindset with a passion for seeing complex algorithms work on real-world hardware.

EDUCATION and/or EXPERIENCE
  • A PhD or MS in Computer Science, Robotics, or a related field, with 2+ years industry experience strongly preferred.
  • A proven track record of successfully deploying learning-based policies on physical robotic systems, especially legged robots or manipulators.
  • Demonstrated experience mentoring or providing technical guidance to other engineers in a team environment.
  • A strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA) is a significant plus.

PHYSICAL REQUIREMENTS
  • Prolonged periods of sitting at a desk and working on a computer
  • Must be able to lift 15 pounds at times
  • Vision to read printed materials and a computer screen
  • Hearing and speech to communicate

*This is a direct hire. Please, no outside Agency solicitations.
Apptronik provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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