Description
We are seeking a highly skilled Staff Robotics Engineer to lead the delivery of vehicle perception and planning capability integrated into our products. You will act as a technical lead, senior individual contributor, and/or team lead, contributing to the design, development, and deployment of safe and effective vehicle autonomy on Anduril's autonomous platforms.
Your responsibilities will include owning customer success through the design and delivery of a multi-year, multi-stakeholder software roadmap, leveraging internal product and program-specific engineering teams to rapidly deliver capability beyond the scope of current platforms, and partnering with external teams to interface requirements between diverse systems and technologies.
As a Staff Robotics Engineer, you will drive the development and implementation of sensor suites, perception algorithms, planning algorithms, and test fixtures to deliver safe navigation and effective operation of Anduril's autonomous vehicles. You will also perform high-impact IC work in architecture and implementation across the whole perception and planning stack, utilising advanced techniques in computer vision, sensor fusion, and machine learning.
You will conduct thorough testing and validation of perception and planning algorithms through development and use of simulation and analysis of data from real-world experiments, including evolving the data analysis tooling. Additionally, you will collaborate with cross-functional teams to ensure effective system integration and testing, and travel to co-locate with end-users and/or other teams up to 20% of the time.
Required qualifications include a Bachelor's degree in Robotics, Mechatronics, Computer Science, Engineering, or a relevant field, or equivalent experience. You must be experienced and proficient in C++ and/or Python software development, familiar with autonomous vehicle hardware and sensors such as radar, sonar, LIDAR, and cameras, and demonstrated knowledge of at least one of computer vision, sensor fusion, SLAM, motion planning, or machine learning.
Preferred qualifications include experience with autonomous systems in the ground, air, maritime, or space domains, experience with simulation tools and frameworks, and knowledge of safety standards and certification processes for autonomous systems.