In this role you will have the opportunity to develop Spot’s next generation autonomy capabilities. You will research & integrate state-of-the-art approaches in the areas of perception, localization and navigation to ensure that our robots can navigate the world robustly and confidently.
You will get to:
Develop Spot’s next generation localization, mapping, perception and autonomy capabilities and deliver them to the product.
Apply and develop novel approaches in the areas of SLAM / ML / Perception to solve complex challenges in semantically-aware navigation and localization in dynamic environments.
Leverage real world sensor data, simulation & tests to ensure that your solutions are robust and performant at scale.
Take active ownership of key components in Spot’s autonomy & perception stack.
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 3+ years of professional experience
A strong understanding of robotics, including methods in perception, localization (SLAM), and navigation. You should be familiar with both traditional and ML-based methods and their typical strengths & shortcomings.
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 and/or navigation/behavior policies.
Experience with Machine Learning frameworks (e.g. PyTorch)
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 advanced robotics, autonomy, and control systems, with a pragmatic approach to deploying robust, real-world solutions.
Experience with advanced topics in localization and navigation, including ML-enhanced methods like semantic SLAM or end-to-end approaches.
Experience with 3D robot simulation (e.g. Mujoco or Isaac Lab).
A track record of relevant product deliverables, open-source contributions or publications.