Staff Machine Learning Engineer

Auror • Denver, CO

5d

About The Position

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.

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.
• An undergraduate degree or higher in statistics, computer science, software engineering, data science, or equivalent practical experience.

Nice To Haves

• 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

Responsibilities

• 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.

Benefits

• Competitive salary
• Employee share scheme
• Flexibility
• Shorter work weeks (at full pay): Everyone gets Friday afternoons off
• Focus on mental and physical health: Wellness Days, and up to $500 for expert sessions every year.
• Health care plan (Medical, Dental & Vision): Auror covers 100% of the cost of your individual health insurance plan with Anthem & Metlife.
• Family-friendly: Comprehensive paid parental leave - 12 weeks for birth parents and 6 weeks for non-birth parents following birth, adoption, or surrogacy, available to all Aurors from day one.
• Personal growth: Support to participate in courses, conferences, or events that will help them develop their skills.
• Team love: Regular team lunches and social events where most (if not all) activities are during work hours.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree