- 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.
- Robust 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

📌 Staff Engineer, Computer Vision, C++ (Melbourne)
🏢 Jobtailor
📍 Melbourne