Senior Engineer, Computer Vision (C++) (R5195)
At a glance
Senior Machine Learning Engineering role at Shield AI. Melbourne · internship.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build bespoke vision algorithms and integrate them into fast C++ pipelines for real-time perception
- Adapt learned models to operational imagery and improve results across changes in lighting, viewpoint and surroundings
- Assess false alarms and missed detections using representative datasets, then use findings to strengthen model robustness
- Tune inference for edge hardware and connect model outputs with C++ perception systems
What you bring
- A degree in computer vision, computer science, engineering or another related technical field
- Deep C++ skills, with a track record building software for high-performance, real-time use
- You have designed and built custom computer vision algorithms, rather than relying solely on prebuilt libraries
- Strong grounding in vision, image processing and machine learning, plus software fundamentals such as algorithms and performance tuning
- You can take unclear technical needs through algorithm design, implementation, integration and delivery
Who this fits
This suits a senior engineer who can turn computer vision concepts into dependable real-time software and work with AI, robotics and optical engineering colleagues. The position is listed as an internship and is based in Melbourne, Australia, with a hybrid arrangement. Offers depend on a cleared background check and may involve reference checks.
From the employer
Job Description:
This role is for a Computer Vision C++ Engineer to support the development of real-time perception capabilities for Shield AI's autonomous systems.
The Computer Vision Engineer will be responsible for designing, developing, and integrating advanced computer vision algorithms into high-performance C++ software pipelines. The role will focus on building custom perception capabilities from the ground up, with an emphasis on real-time performance, reliability, and deployment in edge compute environments. This position is required to increase the team's capacity and technical depth in real-time computer vision, image processing, and applied machine learning.
The successful candidate will bring strong C++ software engineering skills, experience developing high-performance or real-time systems, and a deep understanding of computer vision fundamentals. They should be capable of translating research concepts into deployable software and comfortable working on bespoke algorithms rather than relying only on existing libraries. Experience with areas such as object detection, image classification, target recognition, semantic segmentation, feature extraction, object tracking, video analytics, dataset curation, model evaluation, or deployment of trained perception models would be highly valuable.
The role will also support the development and integration of learned perception models into real-time computer vision pipelines. This may include adapting detection, classification, recognition, or segmentation models for operational imagery; improving model performance across varied lighting, viewpoint, background, and environmental conditions; evaluating false positives and false negatives; and working with representative datasets to improve robustness. Familiarity with combining learned models with classical computer vision techniques, optimizing inference for edge deployment, and integrating model outputs into C++ perception systems would be beneficial. Candidates with a Master's or PhD in Computer Science, Engineering, Robotics, Computer Vision, Machine Learning, or a related field would be well aligned with the technical needs of the team, though strong applied industry experience is also highly relevant.
Required qualifications:
- 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.
Preferred qualifications:
- We do not expect candidates to have all of the following. Experience in any of these areas will help you stand out.
- 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.
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.