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Robotics

Genesis

San Francisco, CAJobNo compensation foundPosted 3mo agoVerified open 3 days ago

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At a glance

Compensation
No compensation found
Location
San Francisco, CA
Work Authorization
Not specified

Job overview

The role designs, implements, and optimizes embedded control stacks for general-purpose robots, creating motion planning and trajectory optimization algorithms, building real-time state estimation pipelines, and developing modular software frameworks. The engineer leads debugging, tuning, and validation on physical robots while integrating hardware, software, and algorithms.

Skills & qualifications

RequiredNice to have

Skills

Motion PlanningOptimal ControlConvex OptimizationSoftware DevelopmentHardware Interface DesignDeep LearningReinforcement LearningParallel ComputingC++Hardware InterfacesSensorsIMUsForce/Torque SensorsMotorsGearboxesDriversDynamicsKinematicsState EstimationTrajectory OptimizationNonlinear MPCVision-Language-Action ModelsParallel Computing on GPUsSimulationHumanoid Robot ExperienceWhole-Body Control SystemsPublished Work in Control Theory

Qualifications

8+ Years Experience

Full job description

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

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