Job Description
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support the development of real-time perception capabilities for Shield AI's autonomous systems.
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designing, developing, and integrating advanced computer vision algorithms into high-performance C++ software pipelines.
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focus on building custom perception capabilities from the ground up, with an emphasis on real-time performance, reliability, and deployment in edge compute environments.
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increase the team's capacity and technical depth in real-time computer vision, image processing, and applied machine learning.
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translate research concepts into deployable software and work on bespoke algorithms rather than relying only on existing libraries.
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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.
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familiarity with photogrammetry, epipolar geometry, bundle adjustment, terrain or map-based registration, and deployment of geometry algorithms into real-time C++ systems.
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Requirements
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Degree in Computer Vision, Computer Science, Engineering, or related technical field.
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Deep proficiency in C++, with proven experience developing software in high-performance, real-time environments.
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Demonstrated experience designing and implementing custom computer vision algorithms from scratch, rather than exclusively applying existing libraries.
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Solid foundational understanding of computer vision, image processing, and machine learning principles.
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Solid software engineering fundamentals, including data structures, algorithms, performance optimization, and version control.
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Proven ability to own technical work from ambiguous requirements through algorithm design, implementation, integration, and delivery.
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Ability to collaborate effectively with multidisciplinary cross-functional teams, including AI experts, robotics engineers, and optical engineers,



to deliver reliable edge solutions.
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Master's or PhD in Computer Science, Engineering, or a related field.
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Experience with object detection, target tracking, 3D reconstruction, SLAM, camera calibration, or behaviour analysis.
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Background in automated video surveillance or other related real-time vision systems.
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Familiarity with industry-standard vision toolkits, such as OpenCV.
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Exposure to deep learning methodologies for image classification, recognition, or sequence modelling.
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Practical experience integrating deep learning models into broader computer vision systems for real-time deployment scenarios.
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Previous experience in the Defence sector, autonomous unmanned systems, or similar mission-critical domains.
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Core Competencies
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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.
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Highest-signal resume keywords
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C++ Programming
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Computer Vision Algorithm Development
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Real-Time Performance Optimization
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Machine Learning Integration
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Collaboration with Cross-Functional Teams
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ATS Optimization Keywords
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Hard Skills
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Computer Vision
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Image Processing
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Deep Learning
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Object Detection
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Target Tracking
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3D Reconstruction
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SLAM
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Camera Calibration
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Performance Optimization
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Version Control
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Soft Skills
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Collaboration
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Problem-Solving
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Technical Ownership
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Certifications & Qualifications
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Master's Degree in Computer Science
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PhD in Engineering
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Industry Keywords
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Autonomous Systems
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Defence Sector
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Automated Video Surveillance
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Mission-Critical Domains
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Tools & Technologies
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OpenCV
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Geometry Algorithms
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Real-Time Systems
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Edge Computing
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📌 Staff Engineer, Computer Vision, C++ (Victoria)
🏢 Jobtailor
📍 Victoria