Machine Learning Engineer

About Auror

At Auror, we’re empowering the retail industry to tackle theft and organised retail crime, a $150 billion problem globally. Founded in New Zealand 11 years ago, we work with leading retailers across North America, Australasia, and the UK to reduce crime through technology for good.

We’re looking for an innovative Machine Learning Engineer who can transform our large‑scale, multi‑modal data into smart, impactful features used by retailers worldwide. You will own the full machine learning lifecycle and build production‑grade systems that help retailers prevent crime, protect their teams, and operate more effectively.

• Designing and deploying machine learning models that connect people, vehicles, and incidents across vast datasets to uncover hidden patterns.
• Detecting and mapping organised retail crime networks using graph analytics, embeddings, and entity resolution techniques.
• Building state‑of‑the‑art image and video understanding systems that power real‑time alerts, evidence linking, and investigative workflows.
• Developing anomaly detection and predictive models that surface emerging threats, unusual behaviours, and actionable intelligence.
• Architecting scalable, multi‑tenant inference platforms that reliably serve models across multiple geographies and cloud environments.
• Taking models from concept to production, continuously monitoring performance, detecting concept drift, improving accuracy, and ensuring fairness and robustness over time.
• Partnering closely with engineers, product managers, designers, and domain experts to embed machine learning into the Auror platform.
• Contributing to responsible AI practices through model governance, explainability, privacy‑preserving approaches, and our Responsible AI Framework.

• Advanced Python programming and strong SQL skills for complex analysis and data manipulation.
• Demonstrated experience designing, deploying, and monitoring at least one ML model in a production environment.
• Ability to communicate complex ML concepts clearly to non-technical stakeholders including product managers, legal, executives, and customers.
• A strong, considered perspective on responsible AI, including fairness, explainability, and the ethical implications of predictive systems applied to human behaviour.
• Deep expertise in computer vision or large‑language models that goes beyond leveraging commodity APIs, with the ability to reason about architecture and trade‑offs at a model level.
• Judgement on when to use pre‑built solutions versus building novel approaches, weighing accuracy, latency, cost, and maintainability.
• Experience with ETL/ELT processes and data engineering tooling, including dbt and Snowflake.
• Comfort working in cloud environments (Azure or GCP preferred) and with containerised applications (Docker).
• Proficiency with Git/Git Hub and collaborative development practices including code review and CI/CD.
• Experience with the full ML lifecycle: dataset construction, feature engineering, model training, evaluation, deployment, monitoring, and retraining utilizing feature stores and model registries.

• Experience testing production ML models for fairness, bias, and accuracy over time, including concept‑drift detection.
• Familiarity with graph or non‑relational databases relevant to network analysis (Neo4j, Elastic Search, CosmosDB, PostgreSQL).
• Experience working with sensitive data across multiple privacy jurisdictions.
• Experience with deep learning and NLP techniques, including libraries such as Tensor Flow and PyTorch.
• An undergraduate degree or higher in statistics, computer science, software engineering, data science, or equivalent practical experience.

• Competitive salary (IC4: $157,500–$197,500).
• Employee share scheme.
• Flexibility and outcome‑focused culture; healthy work/life blend.
• Friday afternoons off at full pay.
• Well‑being support: wellness days and up to $500 for expert sessions annually.
• Health care plan (Medical, Dental & Vision) fully covered by Auror.
• Paid parental leave: 12 weeks for birth parents, 6 weeks for non‑birth parents.
• Personal growth: support for courses, conferences, and events.
• Regular team lunches and social events.

Auror is committed to providing an inclusive and accessible application process to all candidates and we are actively working to improve diversity within the tech industry. We celebrate diversity and inclusiveness at Auror, regardless of race, gender, sexual orientation, family status, religion, ethnicity, national origin, physical disability, veteran status, or age.

Applications will close on the 16th of July 2026.