Software Engineer – ML Infrastructure

The Role

We're looking for a Software Engineer to build and maintain the infrastructure that powers our AI and machine learning workflows. You'll be the bridge between our AI research team and production — building the tooling, pipelines, and deployment systems that let models go from experiment to factory floor. This is a role for someone who thinks in systems but speaks ML: you understand what researchers need, and you know how to build reliable software around it.

What You’ll Do

• Build and maintain the software infrastructure that supports robot learning, including model training, experiment tracking, versioning, and deployment.
• Develop pipelines and tools for collecting, processing, and curating large-scale robotic sensor and telemetry data.
• Support deployment of AI models onto robotic systems, including simulation, hardware integration, runtime monitoring, and feedback loops from field data.
• Build internal tools that accelerate AI engineering workflows across dataset exploration, testing, evaluation, and productionisation.
• Partner closely with AI researchers and robotics engineers to turn model requirements into robust, scalable software systems.

Who You Are

• You have 3–6 years of software engineering experience, with solid exposure to ML infrastructure, MLOps, or AI-enabled systems.
• You write strong production software in Python, and ideally also have experience with C++, ROS, or robotics software stacks.
• You have experience with PyTorch and a practical understanding of the software systems needed to support AI model development.
• You are comfortable with data pipelines, simulation environments, containerised workflows, and GPU compute in Linux environments.
• You enjoy working across AI and robotics, and can support the full path from data collection and testing through to deployment on real systems.