Staff Machine Learning Engineer - Auckland position at Auror.| New Zealand

_{2026-04-21T05:20:34.635Z} bot

Auror Staff Machine Learning Engineer - Auckland

Experience: 11-years

Pattern: Full-time

Country:

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Auckland....New Zealand

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About Auror At Auror, we’re empowering the retail industry to tackle theft and Organised Retail Crime, a $150 Billion problem globally. It’s high volume crime that’s increasingly organised in nature and is putting people, retailers, and communities at risk every day. Founded in New Zealand 11 years ago, we’re working with some of the best and largest retailers in the world across the US, Canada, Australia, New Zealand, and the UK. Auror is connecting people and intelligence to reduce crime. We’re using technology for good. In partnership with our leading retail partners, we need people with the passion, determination, and innovation required to overcome one of the world's largest problems. If you’re looking to make a difference with and for the people dedicated to stopping crime, for good, then we want you on our team. We're also embracing the potential of AI to supercharge our impact—whether that's enhancing the way we detect trends, support our customers, or improve internal workflows. As a company, we're committed to responsibly incorporating AI into how we work and what we build, and we encourage all Aurors to be curious about how AI can elevate their work, regardless of role or function. About The Role We want to arm our retail customers with actionable and unrivaled insight into their business - using real-time data. We currently have 13,500 retail stores using our platform globally with over 50,000 retail users. We are looking for an innovative Machine Learning Engineer to help explore the insights present in our data and use machine learning to deliver smart features at scale. You will work collaboratively with the rest of the data team, product squad, the wider business, and customers at times. You will have the freedom to design and build ML projects from end to end; this includes solution design, data science, working with engineers to operationalise ML, and constantly improving results as algorithms become part of production systems. This is not a research position, this role will be applying machine learning to real world data to help our customers take action on retail crime. Working across multiple jurisdictions and privacy laws, and on sensitive data, we have a focus on being responsible with technology - especially AI. We have created a responsible AI framework and have a core set of guiding principles that help ensure that we - and you - are always thinking about what is the right thing to do. You’ll be reporting to Altieris Peixoto, Data and AI Lead (LinkedIn Link - https://www.linkedin.com/in/altierispeixoto ) I joined Auror with the mission of harnessing data science and Artificial Intelligence to make a meaningful difference to reducing retail crime. My passion lies in leveraging emerging technologies and best practices to design and optimize data-driven solutions that empower organizations to unlock the full potential of their data assets. I thrive in collaborative environments with curious, motivated individuals who embrace continuous learning, enjoy working with modern technologies and methodologies, and are eager to explore innovative and ethical ways to use data. What you will work on: You'll work across a rich, multi-modal dataset including tabular records, free text incident reports, images and video to build and ship production ML systems that help retailers take action. Concretely, that includes: Designing and deploying models that match person and vehicle profiles across incidents. Identifying networks of coordinated retail crime using graph and embedding techniques. Building image and video recognition pipelines for real-time alerting and evidence linking. Applying outlier and anomaly detection to surface unusual patterns in crime event data. Architecting scalable, multi-tenant, multi-geography inference pipelines that operate reliably in production across diverse cloud environments. Continuously improving live models, monitoring for concept drift, evaluating fairness and bias, and closing the loop from production signals back into training. Collaborating with engineering, product, and data teams to integrate ML seamlessly into the Auror platform. Sharing your thinking, documenting designs, presenting to both technical and non-technical audiences, and contributing to our responsible AI framework. What we’re looking for: 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 LLMs that goes beyond leveraging commodity APIs, you can reason about architectures and trade-offs at a model level. Sound judgment 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/GitHub 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. Nice to have: 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, ElasticSearch, CosmosDB, PostgreSQL). Experience working with sensitive data across multiple privacy jurisdictions. Experience of deep learning and NLP techniques, including libraries such as tensorflow and pytorch An undergraduate degree or higher in statistics, computer science, software engineering, data science, or equivalent practical experience. We are looking for people who demonstrate a strong alignment to our Guiding Principles (you can find these on our Careers page ). 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 (but not limited to) race, gender, sexual orientation, family status, religion, ethnicity, national origin, physical disability, veteran status, or age. If you need adjustments to any part of our recruitment process because of accessibility reasons, please do not hesitate to let us know during the application process. We will work with you to identify adjustments that will allow you to perform at your best.

Staff Machine Learning Engineer - Auckland job opportunity at Auror.

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