Principal Engineer, State Estimation (R3260)
Shield AI
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 15 years of related experience with a bachelor’s degree; or 14 years and a master’s degree; or a PhD with 12 years' experience; or equivalent 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.
- You have a demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others.
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