Top Machine Learning Jobs in New Zealand

Lead product strategy and execution for the reconciliation review experience (Auto Bank Rec). Define roadmap, success metrics, and evaluation frameworks; partner with engineering, ML, and UX to shift to management-by-exception; build dashboards and data-driven insights; and expand reconciliation into AI-native, conversational surfaces to accelerate time-to-value.

Provide agricultural science expertise to shape predictive grazing systems: translate biology into testable hypotheses, design and run experiments, validate and interpret models, define measurement protocols, identify new datasets and sensors, and partner with ML engineers, product and data teams to improve model performance and product value for farmers.

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

Lead pre-sales discovery, solution design, estimation and client workshops; define high-level application architectures, mitigate delivery risks, and incorporate AI/ML and generative AI into enterprise solutions. Produce technical proposals, estimates, and reusable consulting frameworks while guiding senior stakeholders and ensuring solutions deliver business outcomes.

Lead pre-sales engagements for Provenir's decisioning platform: conduct customer discovery, design solution architectures, build tailored demos, respond to RFPs, collaborate with Sales, Data Science, and Professional Services, and serve as subject matter expert in credit risk, fraud, and financial crime to drive deals and ensure smooth delivery handoffs.

Provide technology and digital legal advice on procurement, outsourcing, IP, privacy/data protection, cybersecurity incident response, AI/biometric/blockchain projects, commercial negotiations, M&A of tech assets, and IT disputes for complex, cross-border transactions.

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.

10-week onsite engineering internship working with engineers to develop edge-based video AI and imaging solutions, including training AI models, building proofs-of-concept for solar/battery cameras, and applied computer vision research.

Graduate role in Air New Zealand's Data and AI team building skills in AI, machine learning, data science, data engineering and analytics. Collaborate with specialists to solve business problems, develop intelligent solutions for digital products used by millions, and participate in a structured graduate programme with mentorship and rotations.

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.

Own end-to-end development of advanced ML systems for agricultural applications: research, model design, dataset construction, training, deployment, and production monitoring. Collaborate across engineering, product, and design to translate cutting-edge research into practical predictive products for pasture and animal management.

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.

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

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.

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

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.

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.

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.