Object Detection and Tracking Engineer (R5244)

Team: Flight System Integration

Location: London

Commitment: Full Time Employee

Workplace Type: onsite

What you’ll do:

• Develop advanced perception algorithms — Design and implement robust algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities.
• Implement sensor fusion frameworks — Integrate data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness.
• Develop state estimation capabilities — Design and refine algorithms for localization and pose estimation using IMU, GPS, vision, and other onboard sensing inputs to enable stable and accurate navigation.
• Analyze and utilize sensor ICDs — Interpret interface control documents (ICDs) and technical specifications for aircraft-mounted sensors to ensure correct data handling, interpretation, and synchronization.
• Optimize perception performance — Tune and evaluate perception pipelines for performance, robustness, and real-time efficiency in both simulation and real-world environments.
• Support autonomy integration — Work closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules.
• Validate in simulated and operational settings — Leverage synthetic data, simulation environments, and field testing to validate algorithm accuracy and mission readiness.
• Collaborate with hardware and sensor teams — Ensure seamless integration of perception algorithms with onboard compute platforms and diverse sensor payloads.
• Drive innovation in airborne sensing — Contribute novel ideas and state-of-the-art techniques to advance real-time perception capabilities for unmanned aircraft operating in complex, GPS-denied, or contested environments.
• Travel Requirement – Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events). 

Required Qualifications:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience 
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
• Background in implementing algorithms such as Kalman Filters, multi-target tracking, or deep learning-based detection models.
• Familiarity with fusing data from radar, EO/IR cameras, or other sensors using probabilistic or rule-based approaches.
• Familiarity with SLAM, visual-inertial odometry, or sensor-fused localization approaches in real-time applications.
• Ability to interpret and work with Interface Control Documents (ICDs) and hardware integration specs.
• Proficiency with version control, debugging, and test-driven development in cross-functional teams. 

Preferred Qualifications:

• Hands-on integration or algorithm development with airborne sensing systems.
• Experience with ML frameworks such as PyTorch or Tensorflow, particularly for vision-based object detection or classification tasks. * Experience deploying perception software on SWaP-constrained platforms.
• Familiarity with validating perception systems during flight test events or operational environments.
• Understanding of sensing challenges in denied or degraded conditions.
• Exposure to perception applications across air, maritime, and ground platforms. 

Why join Shield AI:

Help build the defining defence technology company of this century.
Work at the forefront of AI, autonomy, and next-generation defence systems.
Operate in a highly entrepreneurial and mission-driven environment.
Make a direct impact on international growth and strategic defence partnerships.
Collaborate with exceptional teams solving some of the world’s most complex operational challenges.