Applied ML Engineer — Real-Time Vision for Safe Driving

Seeing Machines; Canberra; On-site; AUD 120,000 - 180,000; Full time

Job summary

Seeing Machines is seeking an applied Machine Learning Engineer to develop and deploy ML/vision-based features across automotive, fleet and aviation platforms. You will collaborate with researchers, engineers and product owners to ship real-time computer vision solutions for driver monitoring and safety systems.

The role emphasizes hands-on model development, dataset management, and delivering customer‑facing features with a strong ML/CV focus in a global hardware‑driven environment.

Qualifications

• Bachelor’s, Master’s or equivalent in Advanced Computing, Computer Vision, ML or CS.
• Applied ML skills with computer vision experience.
• Strong Python programming ability.
• Excellent problem-solving and communication skills.
• Collaborative, proactive, and cross-team capable.

Responsibilities

• Train and validate ML models for vision-based production software.
• Develop real-time algorithms leveraging ML models to meet use-case needs.
• Direct and curate dataset collection for feature development and validation.
• Investigate product performance issues and propose practical improvements.
• Document high-level feature requirements, architectures and test specs.
• Evaluate state-of-the-art ML models and training techniques.
• Collaborate with ML researchers, software/data engineers, and customer teams.
• Contribute to MLOps and data pipelines using Docker, MLFlow, MetaFlow.

Skills

Applied machine learning

Python

C++

3D geometry

Team collaboration

Education

Bachelor's/Master's in Computing/CS/ML

Tools

Docker

MLFlow

MetaFlow

PyTorch

TensorFlow

LiteRT

ONNX

Metaflow

Streamlit

Job description

Seeing Machines is seeking an applied Machine Learning Engineer to develop and deploy ML/vision-based features across automotive, fleet and aviation platforms. You will collaborate with researchers, engineers and product owners to ship real-time computer vision solutions for driver monitoring and safety systems.

The role emphasizes hands-on model development, dataset management, and delivering customer‑facing features with a strong ML/CV focus in a global hardware‑driven environment.