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 theSpot 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