Senior Robotics AI Engineer

A leading organisation in advanced robotics and physical AI is hiring a Senior Robotics AI Engineer in Singapore. The team is focused on deploying embodied AI solutions on real-world robotic platforms across operational environments, combining foundation models, imitation learning and simulation to deliver scalable, high-performance systems. This is an opportunity to work on production-grade robotics that moves beyond research into real deployment.

Responsibilities:

You will design and develop robust manipulation capabilities for real-world robotic systems, ensuring high success rates, operational safety, and minimal human intervention. This includes owning the end-to-end learning lifecycle from data collection and labelling (for example via teleoperation or demonstrations), through model training and fine-tuning using behaviour cloning and reinforcement learning, to evaluation and deployment.

You will build reliable evaluation frameworks and benchmarks to track performance, prevent regressions, and ensure generalisation across environments and hardware variants. The role also involves integrating AI policies into robot systems, managing compute and latency constraints, and implementing safety mechanisms, failure detection, and recovery pathways.

Requirements

You bring strong hands-on experience with PyTorch and training machine learning models, alongside practical exposure to robotics learning approaches such as imitation learning, reinforcement learning, sim-to-real transfer, or vision-language-action policies. You are comfortable running structured experiments with clear baselines, metrics, and reproducibility standards, and have a disciplined approach to building scalable, maintainable engineering pipelines.

Experience with robotics simulation tools (such as Isaac Sim, MuJoCo or Gazebo), ROS/ROS2, or real-world robot deployment is advantageous, as is familiarity with evaluation tooling, dataset management, or MLOps practices. An interest in solving real-world robotics problems and translating research into production systems is essential.

To apply

To apply, please submit your resume to Samantha Ding at [Confidential Information], quoting the job title. We regret that only shortlisted candidates will be notified.