Robotics Controls Engineer

Atoms•San Francisco, CA

7d•$182,000 - $230,000•Onsite

About The Position

Atoms is building the machines that power the next era of progress. Over the last decade, software has transformed the digital world. But the physical world, where food is made, minerals are mined, goods are moved, and industries are run, remains far less intelligent, far less efficient, and far more constrained. We’re changing that. Atoms builds Physical AI— real-world robots for the industries that move civilization forward, starting with food, mining, and transport. Our systems are designed to understand, predict, and control the real world with precision, turning complex physical operations into something more reliable, more scalable, and more productive. This work requires more than robotics. It requires deep integration across hardware, software, AI, operations, manufacturing, and real estate. We don’t just build machines in a lab. We deploy them into real environments, operate them, learn from them, and improve them until they work at scale. We are roboticists, engineers, operators, and builders. We believe the next great technology companies will not only transform information, but the physical systems that shape everyday life. If you want to work on hard problems with real-world impact, join us.

Requirements

BS, MS, or PhD in Robotics, Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Computer Science, or a related field, or equivalent practical experience.
3+ years of professional, non-internship software development, robotics, controls, or autonomy experience; 3+ years or equivalent demonstrated scope for senior-level consideration.
Strong foundation in classical control theory, including PID control, lead/lag compensation, stability analysis, and frequency-domain or time-domain control design.
Experience with state estimation methods such as Kalman filters, EKF, UKF, sensor fusion, or related probabilistic estimation techniques.
Strong programming skills in C++ and Python for real-time software development, numerical computing, testing, and debugging.
Strong understanding of vehicle dynamics, kinematics, path tracking, longitudinal control, steering control, and actuator limitations.
Ability to read, debug, optimize, and validate real-time control code under strict timing and reliability constraints.
Experience deploying localization, estimation, or controls algorithms on real-world robotic, vehicle, aerospace, or embedded systems.
Ability to analyze system performance using logs, metrics, simulation, replay, and field-test data.
Strong communication and collaboration skills, including the ability to explain technical trade-offs to technical and non-technical partners.
For senior-level candidates, demonstrated ability to lead complex controls projects, define validation or release criteria, coordinate cross-functional execution, and mentor other engineers.

Nice To Haves

Experience with Model Predictive Control, optimal control, or constrained control for real-world systems.
Experience with signal processing, filter design, system identification, controls tuning, or actuator modeling.
Familiarity with trajectory smoothing, path following, motion control, or vehicle control algorithms.
Experience with automotive communication protocols such as CAN, CAN FD, Ethernet, or related vehicle interfaces.
Experience with ROS or similar robotics middleware.
Experience with production autonomy, automotive, aerospace, robotics, or other safety-critical real-time systems.
Familiarity with robotics development infrastructure such as Linux, Git, CI/CD, simulation, log replay, test harnesses, or automated validation pipelines.
Familiarity with modern machine learning techniques applied to controls, estimation, system identification, or vehicle behavior modeling.
Experience with tools or hardware such as NumPy, SciPy, Eigen, NVIDIA Jetson, GPS/RTK, IMUs, CAN interfaces, LiDAR, or radar.

Responsibilities

Design, implement, tune, and validate control algorithms for autonomous vehicle systems.
Develop and maintain state estimation pipelines that fuse multiple sensor modalities and vehicle signals.
Analyze controls performance through simulation, log replay, closed-course testing, and field deployments.
Debug controls, localization, and vehicle behavior issues using logs, metrics, replay tools, and on-vehicle testing.
Identify root causes across controls software, state estimation, vehicle interfaces, sensors, timing, and system integration.
Collaborate with perception, planning, systems, hardware, and operations teams to integrate controls into the broader autonomy stack.
Write safety-critical, production-quality C++ and Python code that runs reliably under real-time constraints.
Define and improve validation methods, performance metrics, release criteria, and regression tests for controls behavior.
At senior levels, serve as a technical owner for production readiness of major controls capabilities or vehicle deployments, including cross-team validation and mentoring other engineers.