The State Estimation & Perception Engineer will be part of the Autonomy Software team at DoorDash Labs, focusing on robotics and automation for last mile logistics. This role involves developing perception and state estimation for package pickup and delivery systems. The engineer will influence system design decisions and work closely with various teams to ensure effective automated operations. A strong background in state estimation and filtering is essential for success in this position.

• Deep experience with state estimation and filtering techniques such as EKF, UKF, MSCKF, and particle filters.
• Experience with optimization-based methods including factor graphs, GTSAM, Ceres, and SymForce.
• Proficiency in visual-inertial odometry (VIO) and/or laser odometry (LIO).
• Strong skills in C++ and/or Rust, with Python for prototyping and analysis.
• A Master's or PhD degree in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a related technical field.

• Own tuning and implementation of the state estimation stack on the drone, including PX4 EKF modifications.
• Develop state estimation and perception for the delivery mechanism, focusing on dynamics modeling and sensor selection.
• Collaborate with controls and planning teams to ensure effective automated pickup and delivery.
• Work with the hardware team to define sensing principles and sensor placement.
• Design and execute flight test campaigns to validate estimator performance.