Top Machine Learning Jobs in New Zealand

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.

Graduate programme to develop future technical leaders through mentorship, rotations across teams, training, and hands-on work on Serato's audio software stack including cloud services, ML, audio, graphics, UI and hardware integration.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

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

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.

The Account Executive will find, win, and grow new customers in the AI/ML sector, managing complex sales cycles and relationships with stakeholders.

Lead delivery of data strategy, advanced analytics and AI engagements; advise senior clients, drive business development, shape practice methodologies, and coach multidisciplinary teams to deliver measurable outcomes.

As a Machine Learning Engineer, develop ML models for computer vision, integrate with products, manage data and experiments, and work on end-to-end ML operations.

The Director of AI Engineering will lead AI capabilities, including development and evaluation of AI systems, while managing a team and collaborating with cross-functional departments.

The role involves conducting impactful research in behavioural information systems, delivering exceptional teaching for undergraduate and postgraduate courses, and supervising graduate research students. A strong publication record and curriculum development experience are required.

Design and implement AI solutions for healthcare, focusing on foundation models and self-supervised learning. Optimize models and training pipelines for scale and rapid experimentation, evaluate generative models, collaborate with engineering and DevOps, follow test-driven agile practices, document progress, and benchmark state-of-the-art techniques to drive product development and clinical impact.

As a Product Owner, you will manage the product backlog, prioritize features, lead cross-functional teams, and ensure data-driven digital solutions that deliver value.

Build and ship end-to-end applied ML and algorithmic solutions for vehicle and parts problems. Develop a foundational model, design robust evaluation and gold datasets, consider production constraints (latency, scale, observability), and partner with product and engineering to deploy reliable, measurable systems that improve over time.

Design, develop, and deploy custom ML models and transformer-based NLP systems. Build and maintain ML pipelines, fine-tune LLMs, implement RAG, monitor production performance, research new techniques, and mentor junior engineers.

Work with the Applied ML team to prototype, evaluate, and ship ML and algorithmic solutions for vehicle and parts problems. Contribute to modelling, ranking, retrieval, evaluation datasets, and production-ready systems while learning engineering best practices and collaborating with product and engineering teams.