Robotics Motion Control Algorithm Intern

About the role

BotsDeploy is working on robotics and AI solutions that help companies simplify and automate operations. This role sits within a team focused on advancing robotic capability through motion-control research and development.

This position is titled Robotics Motion Control Algorithm Intern and is listed to begin on 1.4.2026. The opportunity is marked as an internship and is based in Auckland, New Zealand.

What you will work on

• Design and improve control policies for bimanual manipulation and full-body locomotion using reinforcement learning, imitation learning, and diffusion-policy approaches.
• Build coordination methods for demanding tasks such as carrying objects, handling tools, walking, climbing stairs, and moving across obstacles.
• Run large-scale training and evaluation in advanced simulation environments such as Isaac Lab and MuJoCo.
• Study methods that help policies transfer from simulation to real robots, including deployment on humanoid platforms.
• Explore training approaches for shared policies across multiple tasks, multiple data modes, and multiple robots in order to improve robustness and generalization.
• Work with vision-language-action models to support task interpretation, decision-making, and closed-loop control.

Requirements

• A background in Computer Science, Artificial Intelligence, Mathematics, Robotics, or a closely related discipline is expected.
• Applicants should bring strong programming ability, a solid grasp of algorithms, and good analytical and problem-solving skills.
• Understanding of robot kinematics and dynamics is important, along with familiarity with reinforcement-learning methods used in robotics.
• Hands-on exposure to implementation and optimization in real robotic systems is preferred.
• Experience with deep reinforcement learning or imitation learning techniques such as PPO, SAC, TD3, Dreamer, or GAIL is required or strongly expected.
• Practical knowledge of diffusion-based robot-control approaches such as Diffusion Policy, Guided Diffusion, or Flow Matching is valuable.
• Knowledge of trajectory optimization or control for high-degree-of-freedom robots is needed, especially in motion-control or navigation-related research and development.
• Proficiency in C++, Python, and Linux is required, along with a genuine interest in robotics research.

Additional information

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