Senior Robotics Engineer- Spot Autonomy

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.

• 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 and perception to solve complex challenges in semantically‑aware navigation and localization in dynamic environments.
• Leverage real‑world sensor data, simulation and tests to ensure that your solutions are robust and performant at scale.
• Take active ownership of key components in Spot’s autonomy & perception stack.

We 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 further collaborate with other groups and experts from a wide variety of backgrounds.

• A Master’s 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 and 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 and ViTs and/or navigation/behavior policies.
• Experience with machine learning frameworks (e.g., PyTorch).
• Experience 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.

• A Ph.D. 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 such as 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.