Machine Learning Engineer
Summary
Build and deploy ML models and data pipelines for public-health, environmental, and justice initiatives using Python/R, cloud/Azure, and MLOps best practices.
About The Opportunity
- Join a New Zealand research-based organisation delivering science that supports public health, environmental protection and justice outcomes
- Build and maintain high-quality data and model pipelines, taking proof-of-concept work into production
- Design and implement infrastructure for model management, evaluation and deployment across cloud/HPC/on-prem environments
- Collaborate with data scientists and domain experts across multi-disciplinary programmes
- Promote strong software engineering and MLOps best practice (CI/CD, automation, reliability)
What You’ll Bring
- 3+ years’ experience in data engineering, DevOps/MLOps, or related engineering roles
- Strong capability in Python and/or R, and practical experience deploying ML solutions
- Proven experience building ETL pipelines and repeatable model development workflows
- Confidence with containerisation and automated deployments (e.g., Kubernetes-style environments)
- Understanding of model evaluation, and a solid foundation in statistics
- Comfort working with cloud platforms (Azure experience ideal) and infrastructure-as-code (preferred)
- Ability to embed ethics, privacy, governance and Māori data sovereignty considerations into delivery
What’s On Offer
- Meaningful work: apply ML to complex, high-impact challenges for Aotearoa NZ
- Flexible working options (hybrid environment) and location flexibility across main centres
- Benefits package including equivalent of 5 weeks’ leave, sick leave provisions, and wellbeing support
- Annual volunteer day + supportive, values-led culture focused on collaboration and quality