Robotics

Genesis • San Carlos, CA

1d

About The Position

This role focuses on the design, implementation, and optimization of embedded control systems for general-purpose robots. The position involves developing advanced algorithms for motion planning, trajectory optimization, and real-time state estimation, utilizing optimal control techniques and robust software frameworks. The successful candidate will work directly with physical robots, debugging and validating controllers, and will have the opportunity to explore the integration of deep learning and other advanced AI models into robotic systems.

Requirements

• Passion for your craft and demonstrated excellence in control systems engineering
• Extensive experience in designing, implementing, and deploying advanced control algorithms on real robotic system products (8+ years)
• Deep expertise in dynamics, kinematics, optimal control, and state estimation
• Strong command of hardware interfaces, sensors (IMUs, F/T sensors), and actuation technologies (motors, gearboxes, drivers)
• Production-level mastery of C++ with a track record of building reliable, safety-critical software
• Proven ability to bridge across hardware, software, and algorithms to deliver robust end-to-end systems

Nice To Haves

• An open mind about the power of deep learning, reinforcement learning, and vision-language-action models as critical for general-purpose robotics
• Experience shipping humanoid robots or whole-body control systems
• Impactful published work in control theory, state estimation, or mathematical optimization
• Familiarity with parallel computation on GPUs to accelerate optimization

Responsibilities

• Design, implement, and optimize the embedded control stack for general-purpose robots
• Design motion planning and trajectory optimization algorithms for dynamic locomotion and manipulation
• Build real-time state estimation pipelines for pose, contact, and force sensing, fusing heterogeneous sensor data under noise and uncertainty
• Formulate and solve optimal control problems (nonlinear MPC, convex optimization, trajectory optimization) for high-performance and stable behavior
• Build modular and robust software frameworks enabling rapid iteration between simulation and hardware
• Lead debugging, tuning, and validation of controllers directly on physical robots

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed