Top Machine Learning Jobs in New Zealand

The Machine Learning Engineer will develop predictive models and systems for pasture management, requiring expertise in ML and agricultural knowledge.

Join Welo Data as part of a global community focusing on data annotation and enhancing AI models with diverse linguistic expertise.

Design and maintain scalable ML pipelines, build infrastructure for model serving, implement MLOps, and collaborate with data scientists to optimize models.

The Director of Credit Reporting and Analytics leads data strategy, fraud management, and transformation of credit data into actionable business intelligence, enhancing predictive analytics and supporting various business lines.

The Customer Success Manager at FICO will drive customer retention and expansion, lead onboarding, develop account plans, and analyze customer health metrics.

The Fraud Risk Manager will design and oversee UR's fraud prevention program, manage fraud monitoring, investigations, and implement a governance model. Responsibilities include optimizing recovery workflows, maintaining compliance documentation, and reporting insights to stakeholders.

Develop and design learning paths and courses in various technical domains, authoring materials and assessments while collaborating with team members.

Lead the development and deployment of AI and ML solutions, oversee MLOps strategy, and collaborate with data scientists to enhance data-driven products.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

Lead Demand and Supply Planning functions, optimizing the S&OP process, inventory management, and forecasting accuracy while fostering collaboration across departments.

The intern will design and code AI platforms for training and service, and integrate AI capabilities into gaming through ML Ops processes.

Deliver compelling presentations and host discussions on emerging AI topics, engaging with senior leaders to translate AI concepts into strategic insights.

The Principal Product Manager leads product lifecycle management for brand safety solutions using ML/AI, ensuring effective collaboration and communication across teams.

Anyscale seeks an Enterprise Account Executive to build enterprise client relationships, achieve sales goals, and manage accounts while selling ML cloud solutions.

The intern will assist in integrating AI technologies into gaming, conduct market research, and design innovative applications of AI agents.

The AI Data Specialist role involves data collection, evaluation, annotation, and tagging across various content types while maintaining English proficiency.

Lead the definition and delivery of AI-driven features and solutions. Translate complex needs into clear requirements, prioritize use cases, and coordinate cross-functional teams to deliver effectively.

Lead and develop a global Site Reliability Engineering (SRE) team, ensuring system reliability and performance while driving strategic initiatives and fostering collaboration.

Support cross-functional teams in developing machine learning solutions, mentoring junior engineers, and optimizing ML models using GCP technologies and best practices.

The Machine Learning Engineer will develop and evaluate models, build training pipelines, and enhance performance in a generative media platform, collaborating with teams on AI features.

Lead a cross-functional team to develop and implement AI products, focusing on Large Language Models and enhancing client solutions.

Design and implement ML solutions, fine-tune and integrate LLMs, and collaborate on deploying intelligent features in production environments.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

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.