In this role you will have the opportunity to develop Spot’s next generation autonomy capabilities. You will employ state-of-the-art approaches in computer vision and machine learning to tackle challenging problems in the areas of perception, localization and navigation. 

You will get to:

• Contribute to the development of Spot’s next generation localization, mapping, perception and autonomy capabilities and deliver them to the product

• Develop & apply novel ML-based approaches to solve a variety of challenging problems in the domain of visual perception and semantically-aware navigation

• Help shape the team’s ML model architectures, datasets and pipelines to obtain the best model performances possible

• Write high quality and performant C++ and Python code

• Design and conduct meaningful experiments to ensure we converge on solutions that have state-of-art performance, but are also computationally feasible and robust in real world environments

As a part of the Spot Autonomy Team, you will closely collaborate with other skilled researchers & engineers who are passionate about Spot’s autonomy capabilities. Being embedded in the broader Spot R&D team, you will get a chance to further collaborate with other groups and experts from a wide variety of backgrounds.

To succeed in this role, you should have the following skills and experience

Required:

• A Masters degree in Computer Science, Robotics or related field and 5+ years of professional experience

• First-hand experience in Machine Learning and data driven approaches to visual perception problems. A good understanding of recent ML approaches such as LLMs & ViTs.

• A solid understanding of traditional computer vision, robotics and navigation methods (SLAM) and their typical strengths & shortcomings

• Experience with Machine Learning frameworks (e.g. PyTorch, Onyx)

• Experienced in writing performant, well-structured, and testable C++ and Python code

• Be a team player and good communicator, able to work well in a dynamic and collaborative environment

• Have a passion for quality and autonomous robots

Preferred:

• A PhD in Computer Science, Robotics or related field.

• A strong background in developing and training neural nets

• A strong background in SLAM, and ideally ML-enhanced navigation, such as semantic SLAM.

• A track record of relevant publications or product deliverables