Senior Software Engineer, Data Science – AI Accuracy

DroneDeploy

Senior Software Engineer focused on enhancing AI accuracy through data science and engineering. Building systems to maintain and optimize evaluation datasets in Auckland, New Zealand.

Posted 7/9/2026contractAuckland • 🇳🇿 New ZealandSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python for data manipulation and analysis, SQL for database management, and a strong understanding of evaluation frameworks and prompt engineering. Capable of building robust datasets, conducting error analysis, and optimizing AI product performance through collaborative and iterative development.

Highest-signal resume keywords

Python Data ManipulationSQL Database ManagementEvaluation Dataset DevelopmentPrompt EngineeringError Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLData ManipulationData AnalysisEvaluation FrameworksLabeling SystemsOntology DesignSchema DesignLarge DatasetsVisual Reasoning

Soft Skills

Collaborative MindsetIterative Development

Tools & Technologies

PandasNumPyBraintrustLangfuseAI-Assisted Tools

Industry Keywords

Data ScienceGround-Truth Quality ControlsMeasurement-Path IssuesAI ProductsIndustrial Inspection

Tech Stack

Tools & technologies

NumpyPandasPythonSQL

About the role

Key responsibilities & impact

Build and maintain robust dataset and evaluation infrastructure, including ground-truth quality controls
Diagnose and fix measurement-path issues between offline evals and production accuracy
Iterate on and scale existing labeling frameworks and knowledge capture systems
Own prompt optimization across its full lifecycle, from candidate selection through production rollout and post-launch validation
Automate eval pipelines and build the tooling to run this at scale across multiple AI products
Create reusable internal tooling for error analysis, audits, and experimentation, and prioritize work using likely impact

Requirements

What you’ll need

Strong professional experience with Python for data manipulation, analysis, and tooling (e.g., pandas, NumPy)
Solid SQL and database experience: querying, data modeling, and working with large datasets
A data science background with a knowledge of LLM accuracy and in particular visual reasoning of these models
Building and maintaining 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, from candidate selection through deployment and post-launch validation
Ability to reason about ontology and schema design and its downstream impact on models, evals, and tooling
Domain knowledge in construction or industrial inspection is a plus
A collaborative mindset and a preference for iterative, team-oriented development
Comfortable using AI-assisted tools for coding, data exploration, and debugging, while applying strong engineering judgment to guard against hallucinations and maintain high code quality.

Benefits

Comp & perks

Flexible schedules
Family-friendly benefits
Internal promotions