Seeing Machines (SM) is the world leader in Safety-AI, developing technology that genuinely saves lives. Our state-of-the-art driver monitoring systems are used in millions of vehicles across the globe, providing real-time protection from distraction and fatigue. We work with the world's leading OEMs across multiple transport sectors of automotive, commercial road transport (Fleet), and aviation. In automotive, we enable safer Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) solutions. In Fleet, our best-in-class aftermarket product Guardian provides safety for the drivers and fleet operators, and in aviation, our advanced gaze tracking technology understands how pilots interact and monitor instruments – leading to better training and safer operations.

The Cabin and Camera Features team is part of the Platform Development Group, which is responsible for developing and supporting features that are used in automotive, aviation and fleet products. Examples include camera pose estimation for situations when cameras are mounted on movable items such as a car rear view mirror, and seatbelt detection from a camera system. The team comprises talented multi-disciplinary individuals with skills including software development, machine learning, data science and data acquisition.

We are seeking an outstanding applied Machine Learning Engineer with hands‑on experience developing machine learning / computer vision solutions for real-world problems with a wide impact – technology you develop will be directly deployed on millions of passenger vehicles around the world.

This is a hands-on role, and you will be working closely with a team of machine learning researchers, engineers, data scientists and product owners from diverse backgrounds to develop and deploy our technology in customer products.

You must have a strong drive to learn, experiment, adapt flexibly to changing contexts and focus on delivering features that meet real customer needs.

Your main responsibilities will include:

Training and validating machine learning models that support various vision-based production software features.
Developing and testing real-time algorithms (heuristics) leveraging ML models to meet customer use case requirements.
Directing and curating the collection and use of datasets for feature development and validation.
Deep-diving into product performance issues to identify practical strategies to improve features.
Developing and documenting high-level feature requirements, architectures, designs and test specifications.
Evaluating and employing the latest state of the art ML models and training techniques.
Collaborating closely with other machine learning researchers/engineers, software engineers, data engineers, technicians and customer project teams.
Contributing to MLOps and Data pipelines and engineering practices using tools like Docker, MLFlow, and MetaFlow.

This is a position well-suited to someone who wants to make major technical contributions to the Seeing Machines technology platform while growing their customer and product knowledge and ownership credentials.

Background, Skills, Experience and Qualifications

Mandatory:

Bachelors, Masters or equivalent qualification in Advanced Computing, Computer Vision, Machine Learning, Computer Science, or an equivalent field.
Applied Machine Learning skills, preferably with applications in computer vision.
Strong programming skills and experience developing in Python.
Excellent problem-solving abilities and strong verbal and written communication skills.
A collaborative team player who can work effectively across multiple teams.
A proactive mindset, with an eagerness to try new approaches and solve complex problems.

Desirable:

Experience deploying ML models into production or embedded systems.
Experience with ML training/deployment frameworks such as PyTorch, TensorFlow, LiteRT and ONNX.
Experience reading/writing C++ code and/or developing optimised real-time sensing and processing software.
Experience working in a customer and product-focussed commercial environment.
Experience with Data tools such as Metaflow, Streamlit or equivalent.
Good understanding of 3D geometry and Camera geometry (e.g. coordinate frames, transforms, and 3D–2D projection models).
Experience with agentic coding techniques.

Department: Technology - Platform Development

Locations: Canberra

Date Posted: 07 September, 2026

Computer Vision Jobs in Canberra

Machine Learning Engineer