Robot Control Engineer — Real-Time MPC on Real Hardware

Machenta Ltd; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Meaningful equity

Private health insurance

Free food

Job summary

Machenta Ltd in London is seeking a Member of Technical Staff to advance autonomous robotics control. You’ll design and tune real robot controllers, from torque/impedance to real-time optimal control, collaborating across the stack to deploy on hardware.

You will join a close-knit, ambitious team in King's Cross, contributing to high-impact robotics projects, with ownership over your work and opportunities to shape our hardware-software integration and learning-enabled control methods.

Qualifications

• Hands-on experience designing, testing and deploying controllers on real robots.
• Strong foundation in rigid-body dynamics, control theory and numerical optimisation.
• Experience with optimal control methods such as MPC or trajectory optimisation.
• Proficiency in Python and C++ for real-time systems.

Responsibilities

• Design, implement and tune low-level robot controllers, including torque, impedance and force control.
• Formulate and solve real-time optimal control problems, such as MPC and trajectory optimisation, under tight latency and compute constraints.
• Combine model-based controllers with learned policies to achieve robust behaviour on real hardware.
• Bring up and validate controllers on physical robots, using rigorous testing.
• Help define how the control stack interfaces with our learning systems, shaping how policies and controllers work together across the robot.

Skills

Robotics control design

Rigid-body dynamics

Numerical optimisation

MPC / trajectory optimisation

Python and C++

Real-time systems

Debugging complex systems

Clear communication

Tools

Python

C++

Job description

Machenta Ltd in London is seeking a Member of Technical Staff to advance autonomous robotics control. You’ll design and tune real robot controllers, from torque/impedance to real-time optimal control, collaborating across the stack to deploy on hardware.

You will join a close-knit, ambitious team in King's Cross, contributing to high-impact robotics projects, with ownership over your work and opportunities to shape our hardware-software integration and learning-enabled control methods.