ZipRecruiter

Log In

1

Reinforcement Learning Robotics Jobs in Texas (NOW HIRING)

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will leverage their expertise in ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will focus on achieving ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will focus on achieving ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

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 ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting ... JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving ...

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 ...

webAI Inc

Staff R&D AI Engineer

Austin, TX · On-site +1

Architect and implement reinforcement learning systems for sequential decision-making, including ... Stay current with latest research in VLA models, multimodal AI, and robotics to drive innovation ...

Apptronik

Senior Autonomy Software Engineer

Austin, TX

$190K - $235K/yr

Collaborate with Reinforcement Learning teams to integrate trained policies into real-time robot software stacks. Develop infrastructure for telemetry, logging, evaluation, and replay to understand ...

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 ...

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

... robots to support humanity in every facet of life. The Software Engineer - Human Motion Data will build crucial links between human data and reinforcement learning pipelines, architecting robust ...

next page

Showing results 1-20

All JobsReinforcement Learning Robotics JobsReinforcement Learning Robotics Jobs in Texas

Reinforcement Learning Robotics information

What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?

One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.

What are the key skills and qualifications needed to thrive as a Reinforcement Learning Robotics Engineer, and why are they important?

To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.

What is reinforcement learning in robotics?

Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.

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

AspectReinforcement Learning RoboticsMachine Learning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; knowledge of reinforcement learningDegree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms
Work EnvironmentRobotics labs, manufacturing, autonomous systemsTech companies, data-driven projects, software development
Industry UsageAutonomous robots, industrial automation, researchData analysis, predictive modeling, AI applications

Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.

What are popular job titles related to Reinforcement Learning Robotics jobs in Texas? For Reinforcement Learning Robotics jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Robotics jobs in Texas look for? The top searched job categories for Reinforcement Learning Robotics jobs in Texas are:
What cities in Texas are hiring for Reinforcement Learning Robotics jobs? Cities in Texas with the most Reinforcement Learning Robotics job openings:
Reinforcement Learning Robotics jobs near you
Senior Reinforcement Learning Engineer

Senior Reinforcement Learning Engineer

Apptronik

Austin, TX • On-site

$103K - $142K/yr

Full-time

Posted 12 days ago

Job description

Job Summary:
Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will leverage their expertise in reinforcement learning to solve locomotion and manipulation challenges, mentor junior engineers, and implement advanced learning algorithms for the company's humanoid robots.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
• 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.
Company:
Apptronik is a robotics company that designs and builds humanoid robots for various real-world applications. Founded in 2016, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Growth Stage.

Apply