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.
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