Staff Machine Learning Engineer - Auckland

About The Role

We’re on a mission to give retailers unparalleled visibility into what’s happening across their business, turning real-time data into actionable intelligence that helps them stay one step ahead.

Today, more than 13,500 retail stores and 50,000 retail professionals around the world rely on our platform. The scale and complexity of our data presents an incredible opportunity to uncover patterns, predict outcomes, and build intelligent products that make a real difference in the fight against retail crime.

We're looking for an innovative Machine Learning Engineer who is excited by the challenge of transforming large-scale, multi-modal data into smart, impactful features used by retailers globally. You'll work alongside a talented team of data scientists, engineers, and product leaders to build production-grade machine learning systems that deliver real-world outcomes.

You'll have the freedom to own the entire machine learning lifecycle, from identifying opportunities and designing solutions, through experimentation, model development, deployment, and continuous improvement. You'll be working with a modern cloud-native data and ML platform built on technologies such as Dagster and Apache Iceberg and kubernetes, and industry-leading machine learning tooling, such as pytorch and scikit-learn, giving you the opportunity to solve challenging problems at scale with a contemporary stack.

This isn't a research role. It's about applying machine learning to real-world problems, building practical solutions that help retailers prevent crime, protect their teams, and operate more effectively. Your work will move beyond notebooks and prototypes into production systems that create measurable impact every day.

As we work with sensitive data across multiple countries, legal frameworks, and privacy regimes, responsible innovation is at the heart of everything we do. We've developed a comprehensive Responsible AI Framework and a set of guiding principles that ensure we build technology thoughtfully, ethically, and with trust at the forefront. You'll play an important role in helping us push the boundaries of what's possible with AI while ensuring we always do the right thing.

You’ll be reporting to Altieris Peixoto, Data and AI Lead

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 with one of the most unique retail crime datasets in the world, spanning structured data, free-text incident reports, images, video, and network relationships. Your work will directly power intelligent products that help retailers prevent crime, protect people, and make faster, better decisions. Some of the challenges you'll tackle include:

• Designing and deploying machine learning models that connect people, vehicles, and incidents across vast datasets to uncover patterns that would otherwise remain hidden.
• 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 machine learning 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 seamlessly embed machine learning into the Auror platform.
• Helping shape how we use AI responsibly by contributing to model governance, explainability, privacy-preserving approaches, and our Responsible AI Framework.

This is an opportunity to work on machine learning problems that combine computer vision, natural language processing, graph analytics, anomaly detection, and large-scale distributed systems, all while delivering tangible impact for customers around the world.

Requirements

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 ).

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.