Position Overview:As our
first dedicated State Estimation Engineer, you are the architect of the robot's spatial intelligence. You will own the systems that allow our robots to understand where they are and how they move within complex, unstructured environments.
This is a foundational role. You will bridge the gap between high-frequency sensor data and high-level AI reasoning, ensuring our robots achieve the industry's top generalization and performance.
What You'll Do- Build the Spatial Core: Design and implement robust indoor SLAM and state estimation systems fusing LiDAR, Camera, IMU, and odometry. You will own the full stack, from factor graphs and EKF/UKF to optimization-based methods.
- Sensor Fusion & Calibration: Develop automated pipelines for multi-sensor time-synchronization and calibration (VIO, visual SLAM), ensuring the "Skill Capture" data we collect is ground-truth quality.
- Push the Frontier: Balance robust classical techniques with cutting-edge learned dynamics and neural filtering. You decide when to ship a reliable geometric solution versus when to invest in a differentiable approach.
- Cross-Functional Synergy: Collaborate closely with Perception, Motion Planning, and AI teams to translate raw sensor streams into safe, smooth, and natural robotic motion.
- Production Reliability: Move beyond simulation. You will build the diagnostic infrastructure and validation benchmarks needed to deploy robots into diverse, real-world customer environments.
What You'll Bring- 5+ Years of Real-World Impact: A track record of taking estimation systems from prototype to production on physical hardware (not just in Sim).
- Mathematical Mastery: Deep understanding of spatial math, including 3D rotation representations (SO(3)), frame transformations, and camera projections.
- Software Excellence: Proficiency in C++ for real-time, low-latency systems and Python for rapid tooling and research.
- Ownership Mindset: As the first hire in this domain, you thrive in a fast-paced environment where you define the roadmap and the tech stack.
Bonus Points For- MS/PhD with a focus on SLAM, VIO, or Factor Graphs (e.g., experience with GTSAM).
- Familiarity with state estimation for manipulators or high-degree-of-freedom robotic systems.
- Hands-on experience with learned dynamics or neural-inertial navigation.
Don't let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you're passionate about the intersection of geometry and robotics, we want to hear from you-even if you don't check every box.
