Machine Learning Engineer
Domino’s Pizza, which began in 1960 as a single store location in Ypsilanti, MI, has had a lot to celebrate lately: we’re a reshaped, reenergized brand of honesty, transparency and accountability – not to mention, great food! In the rise to becoming a true technology leader, the brand is now consistently one of the top five companies in online transactions and 65% of our sales in the U.S. are taken through digital channels. The brand continues to ‘deliver the dream’ to local business owners, 90% of which started as delivery drivers and pizza makers in our stores. That’s just the tip of the iceberg…or as we might say, one “slice” of the pie! If this sounds like a brand you’d like to be a part of, consider joining our team!
As a leader of innovation in the food and digital commerce space, Domino’s is constantly testing new concepts, platforms, and technologies that drive outstanding consumer and employee experiences, which requires a disciplined data approach. This position will provide technical proficiency as a Machine Learning (ML) Operations Engineer who focuses on the development and integration of ML enabled software.
The candidate should be an expert in Docker Ops and containerization technologies. They must have knowledge about container orchestration tools like Kubernetes, optimizing Docker image construction for ML performance and CI/CD Pipelines. They will also be responsible for managing and improving our ML application CI/CD pipelines to industry best practices keeping up-to-date with the latest industry trends and technologies. This role functions an internal resource within the Analytics & Insights team support Data Scientist in ML development work.
RESPONSIBILITIES AND DUTIES
(60%) Machine Learning Operations Support
- Work with internal clients and the Data Science team to solve problems using ML.
- Supports ML software build, and optimize applications' containerization and orchestration with Docker and Kubernetes.
- Manage and improve existing automated CI/CD pipelines.
- Helps perform load testing and tuning of AI/ML models and runtime components supporting our production workloads
- Ensures ML microservices are able to access to real time data sources, designing options for data pipelines, as well as analytical packages defined externally from external vendors and desired for use by the A&I data science team.
- Coordinate monitoring of ML/AI model execution performance and optimize reliability of ongoing processing.
(40%) Provide guidance and support / expand use of ML
- Work with internal clients and the Data Science team to solve problems
- Consult with various data science team to architecture solutions, optimize software development, and deploy solutions into production environments.
- Work with development teams to determine requirements to ensure all tracking is in place for future analysis.
- Work as a bridge between data science and IT groups to support integration of AI/ML modeling into production environments.
- Create and execute test plans that help address questions from development teams and troubleshoot.
- Consult inter-departmentally on new product deployments and incremental improvements.
- Master’s degree (or Bachelor’s degree with equivalent experience) in a quantitative science such as statistics, mathematics, computer science, engineering, etc.
- Must have the ability to work independently, with minimal supervision
- Participate in on-call rotations.
- Experience with continuous integration tools and continuous delivery pipeline (e. g. Jenkins, Jfrog, Artifactory)
- At least two years of experience with Kubernetes & Docker in a production environment.
- Experience with container networking on Docker.
- Experience with application deployment by using CI/CD.
- Version control, software experience, Object oriented coding experience
- Experience with streaming data and real-time inference
- Comfortable creating and using APIs and integration into production environments
- Experience scaling a model to production load and monitoring
- Intermediate or Advanced Skills with at least one scripting and/or programming language, e.g. Python, R
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