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Salary
≈ $72k – $115k per year (Estimated)
Location
Hybrid (London, United Kingdom)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Sep 7, 2026. Genesis AI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Headquartered in Palo Alto, California, and Paris, France, Genesis AI is a full-stack physical AI and robotics company specializing in universal foundation models and general-purpose robotic systems. The company develops advanced technologies, including the GENE foundation model and human-scale dexterous hands, to enable automated physical labor. Through its innovative hardware and software ecosystem, its systems are engineered to perform complex, real-world tasks across various industrial and commercial environments.

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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