Robotics

Genesis AI; San Carlos (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Genesis AI is seeking an experienced control systems engineer in the San Carlos, CA area to design, implement, and optimize the embedded control stack for general-purpose robots. You will contribute to motion planning, trajectory optimization, and real-time state estimation while integrating hardware and software into robust end-to-end robotic systems.

The role demands 8+ years in control engineering, strong dynamics/kinematics knowledge, and production-grade C++ expertise.

Qualifications

• 8+ years of experience in control systems engineering.
• Proven track record deploying advanced control algorithms on real robotic systems.
• Strong background in dynamics, kinematics, and optimal control.
• Expertise in state estimation and sensor fusion.
• Proficiency in C++ for production-grade software.
• Ability to bridge hardware, software, and algorithms to deliver end-to-end systems.

Responsibilities

• Design, implement, and optimize embedded control stack for robots.
• Design motion planning and trajectory optimization for dynamic locomotion and manipulation.
• Build real-time state estimation pipelines fusing sensor data.
• Formulate and solve optimal control problems (MPC, trajectory optimization).
• Develop modular software frameworks enabling rapid simulation-to-hardware iteration.
• Lead debugging, tuning, and validation on physical robots.

Skills

Control systems

C++ programming

State estimation

Dynamics & kinematics

Sensor integration

Robotics systems

ML/RL enthusiasm

Hardware interfaces

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