Robotics Software Engineer, Manipulation

We are looking for a senior Robotics Software Engineer to join our clients Manipulation team. In this role you will own and drive development across the full manipulation stack; from grasp planning through trajectory optimization, motion control, and whole-body integration. You will work at the intersection of classical robotics and modern machine learning, translating algorithmic research into reliable, production-ready systems on our clients humanoid platform.

We are looking for someone with strong fundamentals across the modular components of a manipulation pipeline, paired with the engineering discipline and software skill to build robust, production-ready implementations.

This role is focused on manipulation specifically- deep experience in locomotion, multi-robot/fleet coordination, or human-robot interaction and intent-signaling is not a match for what we're hiring for, even if the underlying robotics background is strong.

Your Role:

• Develop and optimize the full manipulation pipeline, integrating perception inputs through grasping, trajectory optimization, motion planning, and control
• Implement robust high-level control strategies for precise manipulation including force/motion control and visual servoin
• Integrate the manipulation pipeline with the humanoid robot's whole-body controller and contribute to loco-manipulation development
• Develop digital twins of manipulation scenes for algorithm development using simulators such as Mu Jo Co  and Isaac Sim
• Conduct rigorous testing in both simulated and real-world environment
• Work closely with the machine learning team to help train and deploy models for advanced manipulation task
• Stay informed about the latest research, leveraging both traditional methods and deep learning-based approaches

We're Looking For:

• BS, MS, or PhD in Robotics, Computer Science, or a related field
• 5+ years of experience in robotics with a strong emphasis on high-level control and manipulation of robotic or humanoid arms (this role sits above actuator-level control, which is owned by a separate team.)
• Strong background in motion planning, control theory, and optimization.
• Demonstrated expertise implementing manipulation algorithms for tasks such as pick-and-place, bin picking, door opening, and similar behaviors deployed and validated on real hardware, ideally at production scale.
• Experience with robotic end-effectors or multi-fingered hands in real-world deployment.
• Proficiency in C++, Python, and relevant robotics libraries (Move It!, cu Motion, Drake, OpenRAVE)
• Experience with trajectory optimization libraries (IPOPT, SNOPT, qpOASES).
• Experience with computer vision algorithms, sensors, point clouds, segmentation, and object detection
• Familiarity with ROS, LCM, or other middleware for robotic systems.

Bonus Qualification

• Experience developing algorithms for contact modeling and force/torque estimation
• Experience with machine learning for manipulation, including behavior cloning and reinforcement learning.
• Publications in top-tier robotics conferences focusing on manipulation systems.
• Experience in a humanoid robot startup environment.