About the company
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.
Responsibilities
- 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.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- Experience with the development and delivery of production-level software systems that feature critical machine learning components.
- Experience with the development of computer vision models, from the data side as well as the model side.
- Experience with end-to-end ML operations, including data acquisition, labeling, model training, pipeline design + management, continuous integration, model versioning, and performance monitoring.
- Experience with leveraging LLMs, LVMs and multimodality models to augment product capabilities, including strong experimentation skills, and the ability to combine off-the-shelf commercial model capabilities with custom ML models.
- Familiarity with methods for ML model validation and verification.
- Experience deploying ML inference infrastructures for systems with high throughput.
- Ability to develop ML-enabled product capabilities in the context of the entire SDLC, from initial concepts through detailed design, development, deployment and maintenance.
Nice to have
- Experience with deep learning frameworks e.g. PyTorch
- Familiarity with inference engines e.g. TensorRT
- Experience with developing edge ML applications
- Experience writing with .NET, C# and Python
Conditions
- Competitive compensation and equity package
- Health insurance
- 5% kiwisaver contribution
- EAP & wellbeing support