Machine Learning Engineer

About The Role

Become part of a New Zealand research organisation dedicated to generating science that informs public health, environmental protection, and justice outcomes. The role focuses on constructing and sustaining robust data and model pipelines, advancing proof-of-concept initiatives into full production. You will also design and develop infrastructure to manage, evaluate, and deploy models across cloud, HPC, and on-premises environments, while collaborating with data scientists and domain experts in multidisciplinary programmes. A strong emphasis is placed on enforcing sound software engineering and MLOps methodologies, including CI/CD, automation, and system reliability.

Key Responsibilities

• Develop and maintain high-quality data and model pipeline solutions.
• Translate experimental models into scalable production systems.
• Create infrastructure to support model management, evaluation, and deployment across diverse computing platforms.
• Collaborate effectively with interdisciplinary teams including data scientists and domain specialists.
• Advocate and uphold best practices in software engineering and MLOps workflows.

Required Skills and Experience

• More than three years' experience in data engineering, DevOps/MLOps, or similar engineering roles.
• Proficient in Python and/or R with practical experience deploying machine learning models.
• Demonstrable ability in building ETL pipelines and establishing repeatable model development procedures.
• Experience with container technologies and automated deployment strategies, such as Kubernetes environments.
• Solid understanding of model evaluation techniques and foundational statistics.
• Comfortable with cloud platforms, preferably Azure, and infrastructure-as-code tools.
• Ability to integrate ethical considerations, privacy, governance, and Māori data sovereignty principles into project delivery.

What We Offer

• Engaging and impactful work applying machine learning to complex challenges specific to Aotearoa New Zealand.
• Flexible hybrid working arrangements and the possibility to locate across main centres.
• A benefits package that includes the equivalent of five weeks' leave, sick leave, and support for wellbeing.
• Annual volunteer day and a supportive culture driven by values, collaboration, and quality.

Additional Information

Applicants must be New Zealand citizens, residents, or possess valid visas allowing work in New Zealand. References will be requested later in the process; do not include them with your application. For further inquiries, contact Imtiaz Mohammed at +64 27 231 8437 referencing Job ID: 18290.