As part of the Research & Advanced Development group, you will research and develop new approaches to solving challenging manipulation problems for real-world robotics systems, allowing them to understand and interact with their environment in unprecedented ways. Your work will contribute to enhancing the capabilities of our robotic solutions and explore new solutions and approaches, unlocking new value we deliver to our customers. This position offers a unique opportunity to work at the cutting edge of robotics applied to real-world challenges.
This role will be onsite at the Bedford, MA office. This position will run from approximately June-December 2025 (dates flexible).We are seeking interns in a variety of disciplines related to robot learning including:
- Imitation learning for complex, agile manipulation behaviors with suction and finger-based grippers
- Reinforcement learning to improve manipulation robustness and dealing with new situations
- AI systems (VLM, other) applied to various warehouse tasks, such as dealing with unexpected situations, dense packing, or error/damage detection.
- Real2sim from large scale production data
- Gripper morphology optimization across large scale product data
In this role you will:
- Perform applied research in robot learning to address real-world warehouse challenges
- Collaborate with other researchers and engineers to apply research findings to our robots
- Leverage production data and our internal development systems to implement and evaluate your solutions
Qualifications
- Currently pursuing an advanced degree (MS or PhD) in Robotics, Machine Learning, Computer Science, or a closely related field.
- Strong software development expertise in Python
- Demonstrated proficiency with major deep learning frameworks such as PyTorch
- Experience with modern machine learning methods such as imitation learning, reinforcement learning, generative models, vision transformers, or related.
- Exposure to developing ML models for hardware interacting with the real world
COOP-2509TK
