Founded in 2015, Shield AI is a venture-backed defense technology company whose mission is to protect service members and civilians with intelligent systems. In pursuit of this mission, Shield AI is building the world’s best AI pilot. Its AI pilot, Hivemind, has flown a fighter jet (F-16), a vertical takeoff and landing drone (V-BAT), and a quadcopter (Nova). The company has offices in San Diego, Dallas, Washington DC and abroad. Shield AI’s products and people are currently in the field actively supporting operations with the U.S. Department of Defense and U.S. allies.
Job Description:
As a member of the HMX Perception 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 onto real hardware that provides robust and accurate estimates of vehicle pose and surroundings for real missions. Shield AI is pushing the envelope by applying advanced AI solutions to real hardware systems. An ideal candidate should aspire to be a part of this industry-changing team developing and deploying advanced technology that can truly make an impact.
What You'll Do:
- Write production quality software in C++
- Produce an Assured Position, Navigation, and Timing (A-PNT) system to enable reliable autonomy in GNSS-degraded or denied environments
- Extend and specialize Shield AI’s state-of-the-art state estimation framework for new sensors, platforms, and missions
- Write test code to validate your software with simulated and real-world data
- Collaborate with hardware and test teams to validate algorithms/code on aerial platforms
- Write analyzers to ingest data and produce statistics to validate code quality
- Enhance sensor models within a high-fidelity simulation environment
- Work in a fast-paced, collaborative, continuous development environment, enhancing analysis and benchmarking capabilities
Required Qualifications:
- BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
- Ability to develop, benchmark, debug, and deploy software-based algorithms
- Demonstrated problem solving skills by applying a scientific approach
- Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; 4 and a Master’s degree; or 2 years and a PhD; or equivalent work experience
- Demonstrated experience integrating and working with sensor payloads in the DoD space
- Proficient with sensor fusion for noisy high-bandwidth exteroceptive sensors on compute-constrained systems
- A solid foundation in theory related to state estimation, object detection, data association, probabilistic robotics, and signal processing.
- Experience working projects with 10+ contributors
- Offers Fast, efficient, effective problem solving approaches
- Exceptional collaborator and communicator
- Comfortability within Unix environments
- Hard-working, trustworthy teammate
- Exhibits holding themselves and others to high standards
- Being kind to others
- Ability to obtain a SECRET clearance
Preferred Qualifications:
- MS or greater in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
- Understanding of robotics technologies related to autonomous behavior development e.g. task allocation or planning.
- Understanding/Experience with unmanned system technologies and accompanying algorithms (specifically air domain)
- Familiarity with high-fidelity simulation and sensor modeling
- Working knowledge of Kalman Filter, Factor Graphs and other modern estimator fundamentals.
- Strong working knowledge of Computer Vision with hands-on experience with OpenCV or similar CV libraries.
- Experience developing sensor effects (control) algorithms.
- Hands-on experience developing or implementing state of the art object detection/recognition pipelines.
- Active SECRET clearance
- Experience with UCI and OMS Standards
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