We are seeking a Senior Research Engineer with a strong robotics learning background to lead research on visuomotor manipulation policies for humanoid robots, with an emphasis on advancing the state of the art while ensuring real-robot deployment.

Key Responsibilities:

• Lead the research and development of learning-based visuomotor policies for humanoid robot manipulation, from problem formulation to real-world validation
• Define research directions and technical roadmaps for manipulation capabilities such as grasping, object reorientation, bimanual manipulation, and assembly
• Advance techniques including behavior cloning, reinforcement learning, and VLA-based reasoning, with a focus on novel contributions and publishable outcomes
• Develop principled approaches to robustness challenges such as sensor noise, partial observability, contact dynamics, and environment variability
• Oversee the research pipeline from data collection strategy and model training to evaluation methodology and deployment
• Manage project milestones, deliverables, and timelines; coordinate with collaborators and stakeholders, and report progress to the PI
• Supervise and mentor research associates, engineers, and PhD students working on the project
• Collaborate with perception, controls, systems, and hardware teams to guide integration of learned policies into the full autonomy stack
• Evaluate tradeoffs between learning-based and classical approaches and make principled architectural and design decisions
• Lead the preparation of publications, technical reports, and grant/project documentation

Job Requirements

• PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
• Strong publication record in robot learning, manipulation, embodied AI, or related areas, demonstrated through publications in internationally recognised peer-reviewed conferences and journals (e.g., CoRL, RSS, ICRA, IROS, NeurIPS, CVPR, or equivalent venues).
• Demonstrated experience developing and deploying robot learning systems on physical robotic platforms.
• Demonstrated expertise in robot manipulation and visuomotor control.
• Strong knowledge of behaviour cloning, reinforcement learning, imitation learning, or other learning-based manipulation methods.
• Proficiency in Python and modern deep learning frameworks such as PyTorch or equivalent.
• Proven ability to independently define research problems, design experiments, analyse results, and drive projects to completion.
• Experience leading, supervising, or mentoring researchers, engineers, students, or project team members.
• Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams.

Preferred Qualifications

• Experience working with humanoid or highly dexterous robotic platforms.
• Experience translating research outcomes into deployed, operational, or commercial robotic systems.
• Track record of successful collaboration with industry or research partners.
• Demonstrated interest in advancing autonomous humanoid robotics through research and real-world deployment.

We regret that only shortlisted candidates will be notified.