You'll be the technical authority on model lifecycle management, working alongside Data Science, Technology, Risk and the wider business. There are no direct reports, so your influence comes from your expertise and the standards you set.
The Role
- Design, build and validate advanced machine learning and generative AI models, leading the most complex, business-critical work
- Define and own the end-to-end MLOps framework, from development and versioning through to release, monitoring and retirement
- Build and maintain automated ML pipelines (CI/CD and continuous training) across Azure, Databricks and Snowflake
- Own the model registry and inventory, so every production model has clear ownership, lineage and approval status
- Lead release management, including shadow, canary and champion/challenger deployments, with rollback plans
- Set up monitoring for drift, performance, fairness, latency and cost, and drive retraining when needed
- Extend MLOps to generative AI, including prompt versioning, evaluation harnesses and guardrails
- Work with Risk, Compliance and Architecture on model risk and responsible AI controls
- Mentor others, set coding and modelling standards, and explain complex topics to senior stakeholders in plain English
What You'll Bring
Must haves
- 6+ years in data science or machine learning engineering, including 2+ years leading MLOps or ML platform work
- Strong Python and SQL, with the ability to review human and AI-generated code
- Deep knowledge of ML methods (GLMs, GAMs, gradient boosting, time series, deep learning) and generative AI
- Hands-on MLOps tooling: MLflow or similar, Azure Machine Learning or Azure AI Foundry, and Databricks
- Solid DevOps skills: CI/CD (Azure DevOps or GitHub Actions), Docker and infrastructure as code
- A track record of running production ML pipelines at enterprise scale, with measurable business results
- Strong influencing skills and the ability to set standards without formal authority
- Insurance, financial services or other regulated industry experience
- Experience with model risk, audit or compliance teams
- A degree in Computer Science, Data Science, Statistics, Engineering or Mathematics (or equivalent experience)
Why This Role
- Real ownership. You'll shape how the models behind pricing, customer and operational decisions are built and run
- A senior technical seat without people management
- Hybrid working, with three days a week in a central Auckland CBD office
- A modern stack and scope to evaluate and recommend new tools and practices
- A genuinely diverse and inclusive workplace
How to Apply
Keen to hear more? Send your CV through Seek, or get in touch with Lesha Grey (leshagrey@momentum.co.nz) for a confidential chat.
To be considered for this role, you must hold New Zealand working rights. We are unable to offer visa sponsorship.
