As a member of the State Estimation team, you will conduct software development at the intersection of classical state estimation techniques, sensor fusion, artificial intelligence, machine learning, and machine perception. You will develop cutting-edge technology that provides robust and accurate estimates of vehicle pose and surroundings at all times in virtually any environment by fusing sensor data from noisy disparate sources.
What you'll do:
- Research and develop world-class state estimation algorithms to advance the state of the art in assured position, navigation, and timing (A-PNT)
- Write production-quality software in C++ that will be deployed on military platforms, ensuring robustness, efficiency, and scalability.
- Develop and maintain comprehensive unit, integration, and system tests to validate your software
- Enhance sensor models within a state-of-the-art simulation environment
- Collaborate with other team members on product roadmap development, feature decomposition, and capacity planning within an agile development framework
- Work in a fast-paced, collaborative, continuous development environment, enhancing analysis and performance benchmarking capabilities
Required Qualifications:
- M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science or a related field; Minimum 2+ years of related professional work experience if you have an M.S degree or 0 years if you have a new Ph.D graduate.
- Proficiency in modern C++ and object-oriented design patterns
- Experience deploying low latency applications to embedded Linux environments
- Experience designing state estimation algorithms (KF, EKF, UKF)
- Familiarity with continuous integration (CI) pipelines and automated testing frameworks in C++
- While familiarity with MATLAB or Python for prototyping and algorithm development is useful, this role demands extensive experience and confidence in deploying production-level code exclusively in C++. Candidates whose primary experience is in MATLAB or Python are unlikely to find this position a good fit.
Preferred Qualifications:
- Deep understanding of state estimation theory and factor graph implementations (e.g., gtsam, ceres)
- Experience developing and deploying inertial- and aided-navigation software to production
- Experience calibrating, characterizing, modeling, and integrating navigational aiding sensor technologies (e.g., IMU, GPS, Barometers, Magnetometers, Laser Altimeters)
- Experience developing vision-based navigation (VBN) and visual inertial odometry (VIO) algorithms
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