About the role

The Opportunity
Join a growing agritech business where accuracy is central to the product, customer trust and future growth.
The technology is live and used across different regions and conditions. What is needed now is one person to own how accuracy is measured, prioritised and improved.

This is a technical, delivery-focused product role. You will work closely with applied science, machine learning and engineering to identify the highest-impact improvements and drive them through to delivery.

Company Profile
This business builds technology used by global agricultural customers to make critical operational and commercial decisions.
Its platform brings together software, computer vision, numeric data and purpose-built hardware to support fruit sizing, grading, yield insights, workforce tracking and orchard management.
The product operates in real-world environments where conditions vary and accuracy matters.

The Role
Working closely with the Head of Applied Science, ML and engineering teams, you will own the accuracy roadmap and delivery pipeline.
You will build trusted measurement frameworks, investigate where performance varies and decide what should be prioritised next.
The answer may sit in an ML model, hardware, sensing, calibration, lighting, onboarding, UX or customer workflows. You will bring these inputs together, form a clear view and influence product and technical roadmaps across the business to get the right solution delivered.

You will scope and sequence work, remove blockers, manage the delivery pipeline and hold teams to agreed commitments, while keeping experimental work moving towards clear outcomes.
The focus is simple: improve accuracy in ways customers can see, trust and value.

Your Fit
You will have come from a genuinely technical role before or alongside moving into product. That could include machine learning, data science, applied science, computer vision, imaging or software engineering.
You understand how ML models are trained, evaluated and improved. You can read performance data critically, challenge technical thinking and turn complex findings into clear priorities.
You have owned software or ML delivery in an environment where the answer was not always known at the start. You are comfortable working directly with engineering and science teams, creating structure and holding delivery to account.

Precision, recall, confidence intervals, regression and hypothesis testing are concepts you can apply to practical decisions.
This could suit a technical Product Manager or an engineer or scientist who has moved into product and is ready for broader ownership.
Experience with computer vision, sensors, hardware, calibration, MLOps, agriculture or horticulture would be useful.

Please note, candidates must have the right to work in New Zealand and be based in Auckland or prepared to relocate.