Senior Engineer, State Estimation

What You'll Do

• Develop and implement advanced sensor algorithms for processing data from IMUs, radar, cameras, GPS, and other sensors.
• Enhance state estimation algorithms by integrating multi-sensor data for improved accuracy and robustness.
• Design and implement real-time sensor data processing pipelines.
• Collaborate with cross-functional teams, including software engineers, autonomy researchers, and hardware engineers, to ensure seamless integration of state estimation algorithms.
• Conduct experiments and field tests to validate the performance of state estimation algorithms in real-world scenarios.
• Stay updated with the latest advancements in sensor technologies and state estimation, applying them to our systems.

Required Qualifications

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience.
• Experience developing and deploying real-time sensor processing algorithms, e.g. with cameras, radar, IMUs, GPS, etc.
• Solid understanding of state estimation techniques, such as Kalman filters, particle filters, etc.
• Experience with C++ 11 or newer.
• Experience with Linux, command line tools, etc.
• Excellent communication skills, with the ability to effectively collaborate with multidisciplinary teams and external stakeholders.
• Proven track record of successfully shipping products, showcasing the ability to navigate through development cycles, overcome obstacles, and deliver high-quality solutions to meet project deadlines and exceed expectations in a fast-paced environment.
• Demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others.
• Ability to obtain a S//SAR level security clearance desired.

Preferred Qualifications

• Experience in implementing inertial navigation algorithms on real-time processing systems.
• Knowledge of computer vision techniques.
• Proficiency in optimizing algorithms for compute-constrained systems.
• Experience with CUDA or other hardware acceleration technologies (e.g. FPGAs).
• Proven track record of transitioning from R&D to production.