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Apptronik is a human-centered robotics company developing AI-powered humanoid robots (Apollo) to support humanity across manufacturing, logistics, healthcare, and beyond. The company operates at the cutting edge of applied AI, tackling the full robotics stack from safety to commercialization and mass production.
As Staff Simulation Engineer for Core Simulation Platform, you will contribute to the architecture and development of a mission-critical simulation platform that serves as the foundation for policy training, controls validation, and CI/CD integration testing. This role requires strong technical leadership and deep expertise in robotics simulation.
Key responsibilities include:
- Contributing to architecture and development of high-performance digital twins that enable rapid policy iteration
- Building and scaling cloud-native simulation pipelines capable of generating millions of experience hours per day, with parallelized physics and rendering
- Improving sim-to-real transfer through advanced contact models and actuator dynamics that help policies trained in simulation transfer to physical humanoid hardware
- Developing sensor-realistic environments (camera, LiDAR, depth) that challenge the perception stack with dynamic and diverse worlds
- Shipping platform improvements that visibly reduce iteration time for RL, controls, and perception teams
- Collaborating with Controls, AI Research, and Perception teams to support their evolving simulation needs
You will work alongside senior team members, applying strong C++ and Python skills, robotics fundamentals, and modern simulator experience to keep the platform robust, performant, and parallel.
REQUIREMENTS:
- Master's or PhD in Computer Science, Robotics, Electrical Engineering, or related field (or equivalent experience)
- 5+ years of experience in robotic simulation, software engineering, or related fields
- 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 and VLAs, 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)
