Machine Learning Engineer

PHF Science

Machine Learning Engineer building AI and data pipelines for PHF Science, a New Zealand public research organisation. Deploying scalable models supporting environmental, public health, and forensic services.

Posted 8/5/2026full-timeAuckland • 🇳🇿 New ZealandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering and MLOps, with advanced proficiency in Python and R for developing machine learning models and data ETL pipelines. Strong foundation in Statistics and experience with CI/CD tools, Azure, and Kubernetes for scalable deployment.

Highest-signal resume keywords

Data EngineeringMLOpsPythonMachine Learning Model DevelopmentCI/CD Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ETL PipelinesMachine Learning Model DevelopmentStatisticsPythonRMLFlowApache AirflowInfrastructure-as-CodeAzureKubernetes

Soft Skills

Problem-SolvingCommunicationTeamworkCollaborationKnowledge Sharing

Tools & Technologies

CI/CD ToolsArgoCDMLFlowApache AirflowAzureKubernetes

Certifications & Qualifications

Post Graduate Qualification

Industry Keywords

Data ScienceEnvironmental ProblemsPublic HealthForensic ProblemsOperational ServicesTe Tiriti o WaitangiTikanga MāoriTe Reo Māori

Tech Stack

Tools & technologies

AirflowApacheAzureETLKubernetesPython

About the role

Key responsibilities & impact

Support PHF Science’s strategy to leverage AI and Data Science for complex environmental, public health, and forensic problems
Build and maintain high-quality data and model development pipelines with the Data Science team
Design and implement infrastructure for efficient management, evaluation, and deployment of models for operational services and research
Translate proof-of-concept data-driven solutions into production-ready systems
Develop data ETL pipelines and machine learning model development workflows
Manage and deploy code, applications, models, and workflows across development and production environments
Collaborate with colleagues and share technical knowledge

Requirements

What you’ll need

A post graduate qualification in a relevant discipline
At least three years of proven experience in data engineering, Dev/ML-Ops or a related field
Expertise and sound understanding of best practices in data and model management and MLOps
Strong foundation in Statistics
Advanced or expert-level proficiency in Python and/or R
Experience with libraries and frameworks for developing Machine Learning models, AI agents, or other data-driven solutions and applications
Experience using CI/CD tools and frameworks such as ArgoCD
Demonstrable track record using MLFlow and Apache Airflow for model and workflow management
Knowledge and/or experience with Azure and Kubernetes for scalable software deployment and management
Experience with Infrastructure-as-code tools is preferred
Demonstrable track record developing data ETL pipelines and machine learning model development workflows
Excellent problem-solving and troubleshooting skills
Strong communication, teamwork, collaboration, and knowledge-sharing skills
Willingness to develop capability in Te Tiriti o Waitangi, tikanga Māori, and/or te reo Māori
Successful applicant must complete a pre-employment drug screen and police records check

Benefits

Comp & perks

Flexible working options to support balancing work and non-work commitments
The equivalent of 5 weeks holidays
15 days sick leave per year and service leave provisions after five years
Annual volunteer day to support an organisation or issue you care about in the community
Free annual flu vaccinations
Life insurance and physical loss benefit
Subsidised Southern Cross insurance & access to special retail discounts
Access to Employee Assistance Programme (EAP), a confidential and free counselling service
Accredited Living Wage employer