Staff Simulation Engineer - Core Simulation Platform

ApptronikSunnyvale, CA
Onsite

About The Position

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.

Requirements

  • Excellent C++ and/or Python programming skills
  • Familiar with software development best practices: CI/CD, automated testing, and code quality standards
  • Understanding of robotics concepts: kinematics, dynamics, controls, system identification
  • Experience with modern robotic simulators (Isaac Lab, MuJoCo, or equivalent)
  • Understanding of Reinforcement Learning with research or production experience
  • Experience with large-scale training workloads — deploying parallel simulations on cloud platforms (AWS, GCP, Azure) with distributed computing frameworks (e.g., Ray, Kubernetes)

Responsibilities

  • Contribute to the architecture and development of the core simulation platform — high-performance digital twins that serve as the foundation for policy training, controls validation, and CI/CD integration testing.
  • Help build and scale cloud-native simulation pipelines capable of generating millions of experience hours per day, parallelizing physics and rendering for rapid policy iteration.
  • Improve sim-to-real transfer through advanced contact models and actuator dynamics that help policies trained in simulation transfer to physical humanoid hardware.
  • Develop sensor-realistic environments (camera, LiDAR, depth) that challenge the perception stack with dynamic and diverse worlds.
  • Ship platform improvements that visibly reduce iteration time for RL, controls, and perception teams.
  • Work with Controls, AI Research, and Perception teams to support their evolving simulation needs as the platform grows.
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