From construction and energy to agriculture, the world’s largest companies use DroneDeploy to simplify field operations, improve safety, and make smarter decisions, faster. By combining aerial drones, 360 and fixed cameras, ground robots and proprietary AI, we’re bringing the power of automation and visual intelligence to all stakeholders, from the field to the boardroom.
At DroneDeploy, we thrive in a mostly remote-first culture rooted in innovation and impact. We’ve been recognized as a Best Place to Work in the SF Bay Area and named one of America’s Great Places to Work—but what truly sets us apart is the experience you gain: solving real-world challenges with cutting-edge technology, surrounded by teammates who are as passionate as they are supportive. Our team is bold, mission-driven, and building something that matters. We foster a culture where a variety of perspectives drive smart decisions, and where growth—both personal and professional—is part of the journey. Whether it’s flexible schedules, family-friendly benefits, or our strong track record of internal promotions, we invest in people as much as we do in product. If you’re looking to be part of something ambitious, authentic, and transformative, you’ll find your place at DroneDeploy.
Role Overview
Build the systems that make DroneDeploy’s AI trustworthy. As a Senior Software Engineer, Data Science on our AI Accuracy team in Auckland, you will be the primary owner of how we measure, understand, and systematically improve the accuracy of LLM-powered features across Progress AI and related products.
You will design and maintain evaluation datasets and pipelines, build internal tools for error analysis and audits, and refine prompts and underlying models from early experiments through to production rollout and post-launch monitoring.
Using your data science and engineering background, you’ll connect ontology and schema design to real-world accuracy outcomes, ensuring that changes in our data and taxonomies propagate cleanly through models, evaluations, and tooling.
This is a six‑month, full‑time contract role focused on making our AI measurably better. You’ll prioritize work by impact, operate with a high degree of ownership over accuracy workflows, and collaborate closely with engineering, product, and Inspection/Progress AI stakeholders. The role reports to the Senior Manager of Software Engineering for AI Insights/Inspection AI.
We champion diversity and encourage candidates of all backgrounds to apply, even if you don’t meet every requirement listed. Share your strengths and tell us how your experience can elevate our AI accuracy work.
Work Environment
Location: Based in Auckland, New Zealand, with strong preference for candidates who can regularly work from our Auckland office alongside the Inspection and Progress AI teams.
Work model: Work In-Office - we support a hybrid approach and expect in‑office presence at least two days per week to stay closely aligned with engineers, PMs, and field-focused partners.
Collaboration: While your schedule offers flexibility, you'll maintain regular overlap with standard Auckland business hours (9:00 a.m.–5:00 p.m.) to enable effective collaboration with local and global teammates and support occasional on-call responsibilities.
Business Travel: Occasional domestic and international travel for team onsites may be required.
AI tooling: AI is built into how engineering work gets done at DroneDeploy. You’ll use AI-assisted tools for coding, data exploration, prompt iteration, and log/debug analysis, while remaining fully accountable for the quality, safety, and maintainability of your solutions.
Responsibilities
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
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.
Drone Certification: Not required for this role.
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