Hybrid Staff Machine Learning Engineer

at Auror

• Job title: Staff Machine Learning Engineer
• Job type: Full Time
• Experience level: Lead
• Salary: $157,500 - $197,500 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Azure, Cloud, Docker, ElasticSearch, ETL, Google Cloud Platform, Neo4j, Postgres, Python, PyTorch, SQL, Tensorflow
• Location requirements: Hybrid, Auckland, New Zealand

About the role

• Machine Learning Engineer at Auror, using data science to reduce retail crime through innovative ML systems. Collaborate with product teams and develop impactful solutions leveraging real-time data.

Responsibilities

• 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.
• 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.

Requirements

• 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.

Benefits

• **Competitive salary Range: **Depending on level of experience (IC4 - $157,500 - $197,500)
• **Employee share scheme: **You’ll own part of a company making a real difference!
• **Flexibility: **We are hard-working and outcome focused, but recognise there is more to life than work. We promote a healthy work/life blend.
• **Shorter work weeks (at full pay): **Everyone gets Friday afternoons off, so you can start your weekend early, and do more of whatever it is that makes you happy.
• **Health Care Plan: **In partnership with Nib, Auror covers 100% of the cost of your individual health insurance plan.
• **Focus on mental and physical health: **We understand how vital our health is and have policies to support your wellness, including: Wellness Days, and up to three expert sessions paid for every year.
• **Family-friendly: **We offer comprehensive parental leave and benefits for primary and non-primary caregivers, including a baby bonus and meals delivered to your door.
• **Personal growth:** We support our team to participate in courses, conferences, or events that will help them develop their skills.
• **Team love: **We have regular team lunches and social events where most (if not all) activities are during work hours.