Staff Engineer, Computer Vision, C++

• support the development of real-time perception capabilities for Shield AI's autonomous systems.
• designing, developing, and integrating advanced computer vision algorithms into high-performance C++ software pipelines.
• focus on building custom perception capabilities from the ground up, with an emphasis on real-time performance, reliability, and deployment in edge compute environments.
• increase the team's capacity and technical depth in real-time computer vision, image processing, and applied machine learning.
• translate research concepts into deployable software and work on bespoke algorithms rather than relying only on existing libraries.
• support the development of geometry-based computer vision pipelines, including applications such as camera modelling, intrinsic and extrinsic calibration, image-to-world projection, geolocation from imagery, visual registration, and multi-sensor spatial alignment.
• familiarity with photogrammetry, epipolar geometry, bundle adjustment, terrain or map-based registration, and deployment of geometry algorithms into real-time C++ systems.

Requirements

• 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.
• 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.

Core Competencies

Demonstrates expertise in developing and integrating advanced computer vision algorithms within high-performance C++ software pipelines, with a strong focus on real-time performance and reliability in edge compute environments. Proven ability to translate research concepts into deployable software and collaborate effectively with multidisciplinary teams.

Highest-signal resume keywords

• C++ Programming
• Computer Vision Algorithm Development
• Real-Time Performance Optimization
• Machine Learning Integration
• Collaboration with Cross-Functional Teams

ATS Optimization Keywords Hard Skills

• Computer Vision
• Image Processing
• Deep Learning
• Object Detection
• Target Tracking
• 3D Reconstruction
• SLAM
• Camera Calibration
• Performance Optimization
• Version Control

Soft Skills

• Collaboration
• Problem-Solving
• Technical Ownership

Certifications & Qualifications

• Master's Degree in Computer Science
• PhD in Engineering

Industry Keywords

• Autonomous Systems
• Defence Sector
• Automated Video Surveillance
• Mission-Critical Domains

Tools & Technologies

• OpenCV
• Geometry Algorithms
• Real-Time Systems
• Edge Computing