Engineering Manager - Controls

EDUCATION and/or EXPERIENCE

• MS or PhD in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or a related field.
• 4+ years of relevant industry experience in robot controls or robotics software (or 2+ years with a PhD), including 1+ year managing engineers and 2+ years as a technical lead.
• PHYSICAL REQUIREMENTS
• Prolonged periods of sitting at a desk and working on a computer
• Must be able to lift 15 pounds at times
• Vision to read printed materials and a computer screen
• Hearing and speech to communicate
• This is a direct hire. Please, no outside Agency solicitations.
• Apptronik provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
• AND REQUIREMENTS
• Technical Skills (Must-Have)
• Controls Background: Strong foundation in robot kinematics, dynamics, and control, with hands-on experience in areas such as whole-body control, manipulation, or teleoperation.
• Real-Time Software: Experience building or leading development of real-time robotic software in C++, including multi-threaded execution, timing, and hardware interfaces.
• Hardware Deployment: A track record of taking control software from simulation to physical robots and supporting it in testing and deployment.
• People Leadership: Experience managing or leading engineers, including hiring, mentoring, performance feedback, and setting team priorities.
• Execution: Experience planning and delivering software in a fast-moving R&D environment, balancing near-term deliverables with long-term code health.
• Good to Have
• Humanoid or Legged Robots: Experience with humanoid, legged, or mobile manipulation platforms.
• State Estimation & System Identification: Experience with state estimation and system identification for robotic systems.
• Learned Policy Integration: Experience integrating reinforcement learning or other learned policies into a real-time control stack.
• Simulation Environments: Experience with physics engines such as MuJoCo, IsaacSim, or Drake.
• Testing Infrastructure: Experience with hardware-in-the-loop testing, continuous integration, and release processes for robotics software.
• Robotics Middleware: Familiarity with ROS 2 or similar robotics middleware.