Staff Software Engineer, Simulation

Location: Hybrid- Any Office (Fremont, CA, Salem, OR, or Pittsburgh, PA); Hybrid- Fremont, CA; Remote

Department: Software Engineering

About the Role

Agility Robotics is building the worlds most capable humanoid robots, and were looking for a senior engineer to help build the simulation software at the foundation of it. Youll be one of the first engineers on a new Simulation team, working alongside the teams leader to shape its technical direction, architecture, and infrastructure from the ground up.

Youll work at the intersection of physics simulation, hardware abstraction, and robot learning, partnering closely with our AI, Controls, Perception Sensors, Hardware Interfaces, Quality Assurance, and Systems Integration teams to build simulation environments that accelerate development, provide insights into the system, and enable rapid validation.

This role can be hybrid (3 days on-site per week at one of our offices) or fully remote, with up to one week of travel per month.

About the Work

• Design, build, and own core components of Agilitys simulation stack as a founding member of the Simulation team
• Develop the hardware abstraction layer connecting sensors, actuators, and physical hardware to simulation environments
• Develop and integrate physics simulators using open-source frameworks, with a focus on fidelity, performance, and sim2real transfer
• Build and maintain high-fidelity models of new and existing robots, including kinematics, dynamics, mass properties, actuator and transmission models, and contact behavior
• Build robust automated pipelines from hardware design, to robot model, to system-identification, allowing new hardware designs to rapidly be used in sim
• Use simulation to train RL policies, generate synthetic data and evaluate end-to-end models
• Use simulation to evaluate proposed robot designs, running trade studies on things like actuator sizing, link geometry, range of motion, and sensor placement, and turn the results into clear recommendations for design teams
• Validate models against physical hardware data and improve fidelity where simulation and reality diverge
• Set a high bar for engineering practices through design reviews, code reviews, and mentorship of other engineers as the team grows

About You

• 5+ years of professional software engineering experience in robotics, including building simulation infrastructure, tooling, or robot models for real-world robotic systems
• Strong proficiency in modern C++ and Python
• Experience with at least one major robotics physics simulator (MuJoCo, Isaac Sim, Gazebo, or similar)
• Experience building rigid-body robot models (URDF, MJCF, USD, or similar), including deriving or validating inertial, joint, and actuator parameters
• Understanding of multibody dynamics and actuator modeling
• Experience with system identification and improving sim2real transfer
• Solid grasp of standard software development practices: Git, CI/CD, Jira or equivalent, feature branching

Collaboration

• Comfortable working across hardware and software teams and translating between different technical vocabularies
• Able to take ambiguous problems, break them down, and drive them to working solutions with minimal direction
• Experience mentoring engineers or leading technical efforts across a small team

Education

• B.S., M.S., or Ph.D. in Robotics, Computer Science, Mechanical Engineering, or a related field

Bonus Points

• Experience with humanoid or legged robots
• Experience with CAD-to-simulation pipelines (e.g., Onshape, SolidWorks, or Creo exports)
• Background in mechanical engineering or mechatronics alongside software
• Advanced degree (M.S. or Ph.D.) with research in simulation, multibody dynamics, or robot modeling
• Experience using simulation to inform hardware design decisions, such as trade studies, requirements analysis, or design-of-experiments

This is a fully remote role with the option to work hybrid if a commutable distance from our Salem, OR, Pittsburgh, PA, or Fremont, CA offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.