Robotics Engineer

This company turns legacy sensor systems into real-time operational intelligence, helping organisations act before threats escalate rather than after the damage is done. Their platform connects to existing cameras and sensors to detect threats and surface insights, all privacy-first and without replacing a single device.

Company mission

Real-time threat detection from the cameras and sensors organisations already have.

Role Overview

Joining the machine learning team in London, you will take ownership of the integration of a new counter-UAS initiative. The role sits at the intersection of robotics, machine learning and systems engineering, and you will own the integration across all three: proving out the concept, building the prototype and taking it into trials, working closely with product partners along the way.

It is a highly interdisciplinary project, and the team cares more about motivation and willingness to learn than ticking every box. If you are strong in some of the areas below and excited to grow into the rest, you fit the brief.

What You'll Own

Concept to Trials

• Proving out the concept, building the prototype and taking it into trials
• Integration across robotics, machine learning and systems engineering
• Working with product partners, suppliers and other stakeholders throughout

Technical Scope

• Machine learning and computer vision
• Sensors and camera modelling
• State estimation and sensor fusion
• Control theory
• Modelling and simulation
• Low-level programming and hardware/software integration

What We're Looking For

Essential

• A degree in robotics, electrical engineering, computer science, mathematics or a related field, or another engineering background backed by hands-on hardware/software integration work
• Strong programming in a low-level language (C, C++ or Rust) plus Python
• A working understanding of modern computer vision, including object detection and tracking, with experience training, optimising and deploying models for real-time or resource-constrained use
• Hands-on state estimation and sensor fusion: Kalman filtering, factor graphs and the problems they underpin, such as SLAM
• A solid grasp of sensors and how to model them, particularly cameras (camera and distortion models)
• Self-directed initiative: you can take an unfamiliar problem, get up to speed through your own research, and document your findings so others can build on them
• Clear communication, including with external partners and suppliers

Useful

• Working knowledge of control theory, particularly designing and tuning PID controllers for closed-loop systems
• Experience developing and testing systems before committing to hardware, from numerical modelling through to 3D simulation
• Familiarity with RF and RF-based sensing, including how RF sensors and sensor arrays work

Get in touch for a confidential conversation. Imogen@waverecruitment.co.uk