Senior Reinforcement Learning Engineer

Apptronik
Austin
Workplace: OnsiteFull timeFunction: Education & TrainingExperience: 5+ yearsEducation: mastersSkills: ["Python","C++","PyTorch","JAX","MuJoCo","IsaacGym","Distributed training","Simulation","Reinforcement learning","Robot dynamics","Control theory"]

Lead hands-on reinforcement learning work on humanoid robotics, deploying state-of-the-art RL algorithms for locomotion and manipulation on physical hardware. Own prototyping-to-deployment cycles, optimize training pipelines, and mentor junior engineers while collaborating with robotics and hardware teams to shape future robot capabilities and performance.

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FursaFursa
Apptronik
Apptronik
6 months ago

Senior Reinforcement Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 6 hours agoStatus: Live
Reposted: similar role first listed 11 months ago

Job Summary

Lead hands-on reinforcement learning work on humanoid robotics, deploying state-of-the-art RL algorithms for locomotion and manipulation on physical hardware. Own prototyping-to-deployment cycles, optimize training pipelines, and mentor junior engineers while collaborating with robotics and hardware teams to shape future robot capabilities and performance.
Location: Austin
Workplace: Onsite
Employment Type: Full time
Job Function: Education & Training
Seniority: Sr. Manager level

Key Responsibilities

  • •Implement and deploy state-of-the-art RL algorithms to achieve world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
  • •Drive the development cycle from prototyping in simulation to transferring and fine-tuning policies on the robot.
  • •Optimize and scale the RL training pipeline for faster iteration and high-throughput simulation and distributed training.
  • •Mentor junior engineers through technical guidance, code reviews, and sharing RL and software development best practices.
  • •Collaborate with robotics and hardware teams to diagnose system-level issues and co-develop solutions for more complex learned behaviors.

Key Requirements

  • •Deep, hands-on expertise (5+ years) with RL frameworks (e.g., PyTorch, JAX) and high-fidelity simulators (e.g., MuJoCo, IsaacGym)
  • •Mastery of Python for rapid prototyping and strong proficiency in C++ for performant, deployable code
  • •Experience building or utilizing large-scale, distributed training pipelines and optimization
  • •Strong theoretical understanding of modern RL, incl. imitation learning, model-based RL, and sim-to-real transfer
  • •Strong intuition for robot dynamics and controls theory and applying these principles to learning-based approaches
Experience:5+ yearsRoboticsReinforcement learningAIHardware
Education:Master's
Skills:PythonC++PyTorchJAXMuJoCoIsaacGymDistributed trainingSimulationReinforcement learningRobot dynamicsControl theory
Languages:English
Tech Stack:PythonC++PyTorchJAXMuJoCoIsaacGymDistributed trainingSimulationReinforcement learning

Company Brief

Apptronik
Develops advanced general-purpose robots and robotic limbs for industrial and commercial applications, combining hardware, actuators, and control software to enable versatile, human-scale robot solutions.
Industry: Robotics
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: Austin, United States
Founded: 2018
WebsiteLinkedIn