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 MuJoCo 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 (MoveIt!, cuMotion, 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.