An Australian-owned tech company that's built a proprietary data platform processing billions of data points a day, pulled in from IoT sensors deployed across some of the world's busiest physical spaces.
Think major airport terminals, stadiums, and smart city infrastructure.
The platform turns raw sensor data into insight on how people move: wayfinding, queue management, passenger flow, operational efficiency.
It's a small, technical team doing genuinely hard computer vision work at scale, with the culture to match: flexible, inclusive, and big on personal development (birthday leave and an annual L&D; allowance included).
Role and responsibilitiesYou'll join the engineering team as a Machine Learning Engineer, working closely with the ML Lead on the company's computer vision roadmap for airport environments.
Day to day that means building and refining models that track movement through terminals in real time, improving flow and adding a layer of automated spatial intelligence to how these spaces are monitored and managed.You'll design and build production codebases and pipelines in Python and C++, apply ML techniques spanning computer vision, spatial analytics and time-series forecasting, and work closely with data engineers and product to ship high-throughput, low-latency solutions.
You'll also help keep engineering standards high: robust code review culture, CI, and solid agile practice.Key technical skills4+ years as a Machine Learning Engineer or Data ScientistStrong Python and SQL, plus hands-on C++ for performance-critical workReal experience with computer vision SDKs,



ideally NVIDIA DeepStream and GStreamer, for real-time video analyticsSolid grounding in ML techniques, statistical analysis, time-series forecasting and deploying real-time inference modelsComfortable with Docker and Kubernetes, cloud infrastructure (AWS preferred)Git, agile ways of working, and the ability to communicate clearly with technical and non-technical stakeholders alikeAn Australian-owned tech company that's built a proprietary data platform processing billions of data points a day, pulled in from IoT sensors deployed across some of the world's busiest physical spaces.
Think major airport terminals, stadiums, and smart city infrastructure.
The platform turns raw sensor data into insight on how people move: wayfinding, queue management, passenger flow, operational efficiency.
It's a small, technical team doing genuinely hard computer vision work at scale, with the culture to match: flexible, inclusive, and big on personal development (birthday leave and an annual L&D; allowance included).
Role and responsibilitiesYou'll join the engineering team as a Machine Learning Engineer, working closely with the ML Lead on the company's computer vision roadmap for airport environments.




Day to day that means building and refining models that track movement through terminals in real time, improving flow and adding a layer of automated spatial intelligence to how these spaces are monitored and managed.You'll design and build production codebases and pipelines in Python and C++, apply ML techniques spanning computer vision, spatial analytics and time-series forecasting, and work closely with data engineers and product to ship high-throughput, low-latency solutions.
You'll also help keep engineering standards high: strong code review culture, CI, and solid agile practice.Key technical skills4+ years as a Machine Learning Engineer or Data ScientistStrong Python and SQL, plus hands-on C++ for performance-critical workReal experience with computer vision SDKs, ideally NVIDIA DeepStream and GStreamer, for real-time video analyticsSolid grounding in ML techniques, statistical analysis, time-series forecasting and deploying real-time inference modelsComfortable with Docker and Kubernetes, cloud infrastructure (AWS preferred)Git, agile ways of working, and the ability to communicate clearly with technical and non-technical stakeholders alikeLocation and packageSurry Hills, Sydney.
Hybrid, 3 days in office.
$160k to $170k package.Be careful - Don't provide your bank or credit card details when applying for jobs.
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📌 Machine Learning Engineer (New South Wales)
🏢 Preacta Recruitment
📍 New South Wales