Machine Learning Engineer

Jora New Zealand will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey. Timescapes is looking for a Machine Learning Engineer to join our small, but growing team of high-performers. We're after someone who approaches problems from first principles, honing in on underlying causes and diligently iterating towards the best solution. We believe that great products feature incredible experiences that customers never want to stop using. Founded in New Zealand in 2017, Timescapes is a visual progress tracking solution for complex construction projects – our mission is to simplify construction through shared visibility. Customers value Timescapes because it helps them stay on schedule, validate construction claims and communicate progress more effectively. We're a rapidly growing company, and are used by some of the largest construction firms across Australia, Canada, New Zealand and the United States. We're deliberate and thoughtful in everything that we do, and we emphasise awareness, speed and quality in our approach to product development. About the Role As our second dedicated ML / AI hire at Timescapes, you'll be working closely with our product and engineering team to develop ML models (computer vision) and incorporate them into our existing (and new) product capabilities. Key aspects of the role include: Working closely with other members of the AI / ML team to design, develop, integrate and support machine learning models, to solve specific construction problems related to tracking activity and progress on civil, institutional and commercial sites. Running experiments with LLMs and other large-scale generative AI models during problem and solution exploration, and determining when to invest in custom development vs leveraging off-the-shelf models. Developing software to manage the ML lifecycle, including data management, labeling and training. Sourcing training data, curating it for quality, and determining how best to integrate it into the ML lifecycle. #J-18808-Ljbffr