Robotics Engineer: Embedded Control & Motion Planning

Genesis AI; Northern (KY); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Genesis AI is seeking a seasoned control systems engineer to design, implement, and optimize the embedded control stack for general-purpose robots. You will craft motion planning and trajectory optimization for dynamic locomotion and manipulation.

You will build real-time state estimation pipelines, solve nonlinear MPC problems, and develop modular software enabling rapid iteration between simulation and hardware.

Qualifications

• Extensive experience in designing, implementing, and deploying advanced control algorithms on real robotic system products (8+ years).
• Strong command of dynamics, kinematics, optimal control, and state estimation.
• Production-level mastery of C++ with a track record of building reliable, safety-critical software.
• Bridge across hardware, software, and algorithms to deliver robust end-to-end systems.
• Open mind about deep learning, reinforcement learning, and vision-language-action models for robotics.

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.
• Formulate and solve optimal control problems (nonlinear MPC, convex optimization, trajectory optimization).
• Build modular software frameworks enabling rapid simulation-to-hardware iteration.
• Lead debugging, tuning, and validation of controllers on physical robots.

Skills

Control systems

C++ development

Dynamics

State estimation

Optimal control

Robotics sensors

Hardware interfaces

Trajectory optimization

GPU parallelization

Deep learning

Reinforcement learning

Job description

Genesis AI is seeking a seasoned control systems engineer to design, implement, and optimize the embedded control stack for general-purpose robots. You will craft motion planning and trajectory optimization for dynamic locomotion and manipulation.

You will build real-time state estimation pipelines, solve nonlinear MPC problems, and develop modular software enabling rapid iteration between simulation and hardware.