# Senior Staff Engineer, Computer Vision

**Company:** [Shield AI](https://hotfix.jobs/companies/shield-ai)
**Location:** Melbourne, Australia
**Role:** AI Research
**Experience:** 7+ years
**Skills:** C++, Computer Vision, Image Processing, Machine Learning, Opencv, Slam, Visual Odometry, Object Detection, Target Tracking, 3D Reconstruction, Camera Calibration, Deep Learning, Data Structures, Algorithms, Version Control
**Posted:** 2026-07-15

> Develop and integrate custom real-time computer vision and perception algorithms in high-performance C++ pipelines for autonomous systems. The role requires strong computer vision, software engineering, and edge deployment expertise, with experience in areas such as SLAM, tracking, reconstruction, or deep learning preferred.

## Job Description

## Responsibilities
- Design, develop, and integrate advanced computer vision algorithms into high-performance C++ software pipelines.
- Build custom perception capabilities for real-time performance, reliability, and deployment in edge compute environments.
- Develop tracking and spatial perception pipelines for autonomous systems, including visual localization, motion estimation, scene reconstruction, landmark tracking, map building, and perception-assisted navigation.
- Translate research concepts into deployable software and develop bespoke algorithms rather than relying exclusively on existing libraries.
- Own technical work from ambiguous requirements through algorithm design, implementation, integration, and delivery.
- Collaborate with AI experts, robotics engineers, optical engineers, and other multidisciplinary teams to deliver reliable edge solutions.

## Requirements
- Degree in Computer Vision, Computer Science, Engineering, or a related technical field.
- Deep proficiency in C++ and experience developing software in high-performance, real-time environments.
- Experience designing and implementing custom computer vision algorithms from scratch.
- Strong understanding of computer vision, image processing, and machine learning principles.
- Strong software engineering fundamentals, including data structures, algorithms, performance optimization, and version control.

## Preferred Qualifications
- 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 related real-time vision systems.
- Familiarity with OpenCV or other industry-standard vision toolkits.
- Exposure to deep learning for image classification, recognition, or sequence modelling.
- Experience integrating deep learning models into broader computer vision systems for real-time deployment.
- Experience in the defence sector, autonomous unmanned systems, or similar mission-critical domains.

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