Top Machine Learning Jobs in New Zealand

Own an end-to-end product domain: discover high-impact customer problems, define value, and deliver hardware, firmware and software solutions. Lead continuous discovery with engineering and design, engage directly with farmers, set priorities and strategy, leverage AI/automation, and communicate product vision to stakeholders.

As a Junior Data Scientist, you will build models to predict hardware failures, analyze performance, and provide insights to support decision-making and cross-functional collaboration.

Develop end-to-end machine learning pipelines and advanced models for pasture growth, biomass estimation, and farm operations. Conduct research and literature reviews, design datasets and architectures, deploy and monitor production systems, and collaborate with engineering, product and design to deliver farmer-facing insights and recommendations.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The role focuses on MLOps, collaborating with teams to build ML systems, maintain scalable infrastructure, and ensure model reliability. Responsibilities include developing tools, managing cloud costs, and supporting data scientists in ML implementation.

The Senior Data Scientist will enhance survey operations, analyze data quality, run experiments, and collaborate with cross-functional teams to solve business problems using advanced data science techniques.

As a Data Scientist at Tracksuit, you will scale survey operations, apply statistical techniques, build data quality systems, and collaborate with product teams to develop brand measurement solutions.

Lead the Data Operations team to design, build, and manage ground truth datasets for machine learning, ensuring data quality and operational efficiency.

Design and maintain scalable ML pipelines, build model serving infrastructure, implement MLOps practices, manage data quality, and optimize model performance.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a Software Engineer, you'll enhance the user experience of ML tools, optimize workflows, and collaborate with product managers on ML infrastructure projects.

Own end-to-end ML projects focused on recommendation and LTV signals: develop, evaluate, and deploy models; build training/scoring pipelines; run A/B tests; monitor production models; collaborate with product and analytics; mentor colleagues.

As a Robotics Machine Learning Engineer, you will build data pipelines, run demos, and ensure customer satisfaction while evolving product features based on client needs.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

As a Senior Machine Learning Engineer, you'll manage the ML lifecycle, develop ML models, collaborate with teams, and optimize systems for production deployment.