Create reusable internal tooling for error analysis, audits, and experimentation.
Iterate on and scale existing labeling frameworks and knowledge capture systems.
Analyze how changes to our ontology and schema propagate across models and infrastructure.
Prioritize work by likely impact.
What we’re looking for
Strong professional experience with Python for data manipulation, analysis, and tooling (for example, pandas and NumPy).
Solid SQL and database experience, including querying, data modeling, and working with large datasets.
A data science background with knowledge of LLM accuracy, particularly visual reasoning.
Experience building evaluation datasets, running and debugging evals with tools such as Braintrust or Langfuse, and conducting error analysis.
Experience designing ground-truth and labeling systems, and measuring label agreement and data quality.
Familiarity with prompt engineering and the full prompt lifecycle, plus the ability to reason about ontology and schema design and its downstream impact.
A collaborative, ownership-driven mindset with a preference for iterative, team-oriented development. Construction or industrial inspection domain knowledge is a plus.
Location in Auckland, with at least 2 days per week in the office, good overlap with our 9–5 schedule, occasional on-call support, and occasional domestic and international travel.
Additional Information
Base Pay Range
92,000.00 - 126,500.00 NZD Annual
This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate’s job-related skills, experience, education or training, and location.