Compensation Overview

Are you captivated by the idea of a synthetic world where robots and virtual humans coexist seamlessly? Do you stay abreast of the latest in efficient and accurate contact simulation and eagerly delve into the specs of cutting-edge graphics cards to push the boundaries of your simulation tools? Is your passion centered around crafting simulation tools that propel the advancement and real-world application of robots?

At Collaborative Robotics, simulation is the heartbeat of our innovation, enabling us to forge robots that are trusted companions, seamlessly integrating into human environments. As the Simulation Lead, you will play a pivotal role in defining and refining our simulation methodologies, fostering the creation of digital twins.

Collaborative Robotics is a team of innovators and builders redefining the future of human-robot interaction. We are working to realize a world where robots are a trusted extension of your surroundings. They work, adapt, and react around you. Not the other way around.

This role is located at our Santa Clara, CA headquarters, or remotely within the US.

Key Responsibilities:

• Own the simulation foundation for developing a trustworthy robot.
• Define our approach to modeling the robot and the world in simulation.
• Develop and oversee the tooling that enables the creation and testing of full digital twins

Minimum Qualifications:

• Bachelor’s degree in Computer Science or a related technical field.
• At least 4 years of experience working within engineering teams.
• Demonstrated experience with simulation frameworks and applying simulations to expedite real robot development.
• Comprehensive skill set ranging from GPU utilization to 3D asset modeling.
• Proficiency in Python or C++, with a readiness to learn new languages or technologies.
• Solid foundation in mathematics, encompassing 3D geometry, linear algebra, probability theory, physics, dynamics, and numerical modeling.
• Enjoys working in a fast paced, collaborative and dynamic start-up environment as part of a small team.
• Pragmatic and customer-focused approach.

Preferred Qualifications:

• Advanced degree (Master’s or PhD) in Computer Science, Computer Engineering, or Electrical Engineering.
• Expertise in dynamic physical system modeling and simulation, including contact, collision, controls, dynamics, sensor and actuator modeling.
• Experience with large-scale parallel simulations for deep learning model training.
• Familiarity with Isaac and/or Ignition/Gazebo simulation environments.
• Knowledge of sim-to-real comparisons, fidelity assessments, and validation techniques.
• Proficiency with ROS2 and low-level physics APIs.
• Background in engineering management, machine learning, design, and architecture.
• Proven experience in robotic or autonomous vehicle simulation projects.

The base salary range for this position is $185,000 - $225,000 plus equity and comprehensive benefits. Our salary ranges are determined by role and experience level. The range reflects the minimum and maximum target for new hire salaries for the position across the US. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.