Staff Software Engineer, Controls Company Genesis is a global physical AI lab and full-stack robotics company. We build generalist robots to unlock unlimited physical labor, allowing humans to focus on creativity, curiosity, and what they love. We recently raised a $105M Seed round backed by Khosla Ventures and Eclipse, and we’re looking to expand our software and hardware teams rapidly. What You’ll Do • 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 You’ll Bring • 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 • An open mind about the power of deep learning, reinforcement learning, and vision-language-action models as critical for general-purpose robotics • Bonus: Experience shipping humanoid robots or whole-body control systems • Bonus: Impactful published work in control theory, state estimation, or mathematical optimization • Bonus: Familiarity with parallel computation on GPUs to accelerate optimization