Senior Robotics Systems Engineer

We are building the infrastructure and tooling that powers Physical AI systems from large-scale robotics data collection and perception pipelines to simulation environments and sim-to-real deployment workflows. As a Senior Robotics Systems Engineer, you will work at the intersection of robotics, data infrastructure, perception, and AI. You'll design systems that capture, validate, process, and replay multimodal robotics data, build tools for robotics developers and researchers, and help bridge the gap between simulation and real-world robotic deployment. This role is ideal for engineers who enjoy working with real robots, large sensor datasets, and the infrastructure required to train and evaluate next-generation robotic AI systems.

Responsibilities:

• Design and build robotics data collection platforms for real-world robot operations.
• Develop tooling for recording, replaying, debugging, visualising, and analysing robotics datasets.
• Build scalable pipelines for ingestion, processing, storage, and retrieval of multimodal robotics data.
• Create offline evaluation frameworks, dataset validation systems, and perception debugging workflows.
• Work with point clouds, camera streams, IMU, LiDAR, depth sensors, and other robotics modalities.
• Develop systems for sensor synchronisation, calibration, timestamp alignment, and data quality assurance.
• Build internal visualisation and developer tools using modern web technologies.
• Support simulation-to-reality Sim2Real) and reality-to-simulation Real2Sim) workflows.
• Integrate perception and AI models into robotic platforms and production environments.
• Collaborate with robotics, AI, and infrastructure teams to improve model performance through better data and evaluation systems.
• Implement monitoring, safety mechanisms, and operational guardrails for autonomous robotic systems.

Requirements:

• 4+ years of professional experience in robotics software engineering.
• Strong experience with ROS and/or ROS 2
• Hands-on experience with robotics data formats such as rosbag and MCAP.
• Experience working with real robot deployments and production robotics systems.
• Strong Python engineering skills.
• Experience building distributed systems, backend services, or large-scale data infrastructure.
• Experience with 3D perception and point cloud processing using tools such as PCL or Open3D.
• Experience designing data collection, replay, and robotics debugging workflows.
• Experience with multimodal robotics datasets and perception pipelines.
• Experience with sensor fusion, synchronisation, calibration, and timestamp management.
• Experience building internal developer tools, visualisation systems, or robotics debugging interfaces.

Preferred Qualifications:

• Experience in building robotics training or data collection laboratories.
• Experience with large-scale robotics dataset management and curation.
• Experience with offline evaluation systems and benchmarking infrastructure.
• Strong C experience in robotics environments.
• Experience deploying foundation models, VLMs, VLAs, or multimodal AI systems onto robotic platforms.
• Experience connecting AI inference systems with robot control stacks and motor controllers.
• Familiarity with NVIDIA Isaac Sim, Omniverse, MuJoCo, Gazebo, or other robotics simulation platforms.
• Experience developing Sim2Real and Real2Sim workflows.
• Experience with autonomous navigation, manipulation, or embodied AI systems.
• Experience implementing safety systems, fail-safe mechanisms, and operational monitoring for robotic deployments.

Nice-to-Have Experience:

• Robotics fleet operations.
• Teleoperation systems.
• Data engines for robotic learning.
• Synthetic data generation.
• Reinforcement learning pipelines.
• World models and embodied AI systems.
• Large-scale robotics infrastructure supporting hundreds of robots or petabyte-scale datasets.

Skills

Python, ROS, ROS2, robotics