Robotics Engineer (planning & behaviour)

Robotics Engineer (planning & behaviour)

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Robotics Engineer (planning & behaviour)

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Robotics Engineer (planning & behaviour)

Department

Behaviour

Job Type

Full-time

Location

Cambridge

Modality

3 days on-site

Start Date

01/02/2026

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We are looking for a Robotics Engineer to join our Behaviour Team. You will build the core planning and action-execution capabilities of the Mastermind system. This role is responsible for the full stack of robotic behaviour, from high-level strategic planning down to the interaction with low-level motion control sub-processes. You will architect and implement both a task manager, which determines the multi-agent strategy to achieve a mission, and a behaviour manager, which translates those strategies into collision-free physical motion for our fleet of robots.

From the 3 layers of robotic behavior, this position is mostly to work in the behaviour (i.e. symbolic planning layer) while touching a little of motion (path) planning and control.

behaviour planning

motion (path) planning

control

💡

Note: you will not need to touch or implement low level proportional or PID controllers.

Who we are

About the Role

What you'll get to do

Strategic Task Planning: Design and implement multi-agent planning algorithms that decompose complex mission goals into a sequence of high-level tasks for the robotic team. Integrate and manage a library of diverse navigation stacks (e.g. Nav2) to plan and execute paths and perform complex tasks. You'll be building hierarchical behavior trees that decompose complex multi-agent tasks into smaller components.

Motion single-robot Planners: use motion planners for programming individual (single robot) navigation stacks (e.g., TEB planner) and manipulation planners (e.g., MovIt).

Action Abstraction: Define a clear hierarchical interface between high-level strategic tasks and the low-level robotic actions required to execute them (e.g. using PDDL).

Feasibility and Validation: Implement the geometric reasoning and feasibility checks to verify that actions are physically possible, providing critical feedback to the system to trigger adaptive responses.

What we'd like to see

MSc or PhD in Robotics, Computer Science, or a related engineering field.

A strong, demonstrable background in robotics planning, spanning both high-level task planning and low-level motion planning, control, and kinematics.

Experience with simulation tools and workflows (Isaac Lab preferably, MuJoCo, SAPIEN, Gazebo are also relevant).

Reinforcement learning , behaviour trees, finite state machines and automated planning (e.g. using PDDL).

Extensive, hands-on experience with ROS 2 and standard planning frameworks within its ecosystem (e.g., Nav2, MoveIt).

Familiarity with collision checking, obstacle avoidance techniques, and geometric data structures used in planning.

Excellent, production-quality programming skills in C++ and Python.

What will set you apart

Practical experience with symbolic AI planners or formal planning languages like PDDL.

Experience in multi-agent planning, task allocation, or auction-based mechanisms.

A background in trajectory optimization or optimal control theory.

Experience developing custom controllers and planners for real-world robotic hardware.

Motion Planning & Control: Design and implement software that translates high-level behavioral requests into executable, low-level commands for various robotic platforms (e.g., vehicles running PX4).

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