Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check.
Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
Required qualifications:
Degree in Computer Vision, Computer Science, Engineering, or related technical field.
Deep proficiency in C++, with proven experience developing software in high-performance, real-time environments.
Demonstrated experience designing and implementing custom computer vision algorithms from scratch, rather than exclusively applying existing libraries.
Solid foundational understanding of computer vision, image processing, and machine learning principles.
Strong software engineering fundamentals, including data structures, algorithms, performance optimization, and version control.
Proven ability to own technical work from ambiguous requirements through algorithm design, implementation, integration, and delivery.
Ability to collaborate effectively with multidisciplinary cross-functional teams, including AI experts, robotics engineers, and optical engineers, to deliver reliable edge solutions.
Preferred qualifications:
We do not expect candidates to have all of the following. Experience in any of these areas will help you stand out.
Master’s or PhD in Computer Science, Engineering, or a related field.
Experience with object detection, target tracking, 3D reconstruction, SLAM, camera calibration, or behaviour analysis.
Background in automated video surveillance or other related real-time vision systems.
Familiarity with industry-standard vision toolkits, such as OpenCV.
Exposure to deep learning methodologies for image classification, recognition, or sequence modelling.
Practical experience integrating deep learning models into broader computer vision systems for real-time deployment scenarios.
Previous experience in the Defence sector, autonomous unmanned systems, or similar mission-critical domains.