Machine Learning Robotics Engineer

Job Description

• The Machine Learning Robotics Engineer is responsible for developing AI-driven algorithms and software that enable intelligent robotic systems to perceive, learn, and make autonomous decisions.
• This role combines robotics, computer vision, machine learning, and control systems to enhance automation capabilities across industries such as manufacturing, logistics, healthcare, automotive, and aerospace.
• This is a remote UK-based role, with occasional travel for on-site integration, testing, or customer support.

Key Responsibilities

AI & Machine Learning Development

• Design, develop, and deploy machine learning models for robotic perception, navigation, manipulation, and decision-making.
• Build deep learning models for object detection, classification, segmentation, tracking, and scene understanding.
• Implement reinforcement learning and behaviour-planning algorithms to improve autonomous performance.

Robotics & Autonomous Systems

• Develop core robotics algorithms including SLAM (Simultaneous Localization and Mapping), motion planning, obstacle avoidance, sensor fusion, and control strategies.
• Integrate ML-based models into robotics platforms such as AMRs, AGVs, robotic arms, drones, and autonomous vehicles.
• Collaborate with robotics hardware teams to optimize AI models for real-world robotic constraints.

Software Engineering

• Write production-quality code in Python and/or C++, using frameworks such as ROS/ROS2, OpenCV, PCL, and robotics middleware.
• Develop simulation environments using Gazebo, Isaac Sim, Webots, Unity, CARLA, or AirSim to test ML and robotics algorithms.
• Optimise models for real-time performance on edge computing platforms (NVIDIA Jetson, ARM devices, embedded GPU systems).

Testing, Validation & Deployment

• Create test plans and evaluate system performance using both simulated and real-world data.
• Conduct experiments to validate algorithm accuracy, robustness, and scalability.
• Document findings, performance metrics, and recommendations for system improvements.

Cross-Functional Collaboration

• Work closely with AI researchers, robotics engineers, product managers, and software teams across the UK and EU.
• Participate in design reviews, technical discussions, and collaborative problem-solving.
• Support integration and deployment of robot autonomy solutions for clients and internal teams.

Required Qualifications

• Bachelor's/Master's degree in Robotics, Computer Science, AI, Machine Learning, Electrical Engineering, or related fields.
• 2–5+ years hands-on experience in:
• Robotics software development
• Machine learning or computer vision
• Autonomous systems engineering
• Strong expertise in: Python, C++, ROS/ROS2, ML frameworks (TensorFlow, PyTorch), SLAM, path planning & control systems
• Deep learning for perception tasks
• Experience working with sensors: LiDAR, RGB/Depth cameras, IMUs, radar, GPS.