Top Machine Learning Jobs in New Zealand

As a Software (ML Product) Engineer at iterative.ai, you will enhance user workflows for DVC, collaborate with technical product managers, and improve MLOps practices within ML teams. Responsibilities include optimizing the tool’s usability and driving projects like dvclive, emphasizing software engineering skills and communication.

The Senior Statistical Data Scientist will provide technical leadership in developing analytics solutions, conduct statistical analysis, build models, and collaborate with teams to integrate statistical insights into workflows. The role requires mentoring team members and applying advanced statistics and machine learning to solve business problems.

As a Statistical Data Scientist, you will develop innovative data solutions, conduct statistical analysis, build predictive models, and create visualizations to support business decisions. You'll work cross-functionally to integrate data science solutions into existing workflows and provide expert guidance on data projects.

As an Engineering Manager, you will lead multiple product teams focused on vegetation management and data ingestion by managing a team of engineers. You will foster a collaborative environment, provide support and coaching, make strategic technical decisions, and improve engineering practices while aligning with product managers' goals.

The Head of Solutions Implementation will manage client relationships, lead project teams, drive business development, and mentor team members. This role involves strategic planning, contributing to the firm's methodologies, and enhancing client solutions through advanced data analysis and automation.

The AI/ML and MLOps Field Engineer at Canonical will assist global companies in adopting AI using open source technologies on cloud infrastructures, primarily focusing on Linux and Kubernetes. Responsibilities include architecting cloud solutions, engaging in customer interactions, and solving complex data architecture problems using various data technologies.

The DDF Engineering Lead will oversee a team of data engineers and DevOps engineers, driving the delivery of data products and implementing DataOps practices. Responsibilities include collaborating with cross-functional teams, optimizing data pipelines, ensuring adherence to governance policies, and promoting data quality. This role requires significant technical leadership and stakeholder engagement to maximize data utilization for business value.