Staff Machine Learning Engineer

Summit Health•Minneapolis, MN

1d•Hybrid

About The Position

As a Staff Machine Learning Engineer on Shipt's Personalization Platform team, you will drive key AI initiatives. In this role, you’ll collaborate with Data Scientists to design and deploy intelligent, personalized recommendation models to drive user engagement across Shipt. You will be a hands-on senior technical contributor in the Membership organization and your work will consist of contribution to architecture, design, and implementation to deliver high quality AI driven solutions in a rapidly evolving marketplace environment. In this role you will design, build and maintain scalable ML infrastructure and production systems as well as closely collaborate with Data Scientists to architect data pipelines for serving and training ML models for Shipt's Personalization Platform. You will also be responsible for leading the team to build scalable, low-latency, and fault-tolerant systems to serve real-time recommendations at scale and developing robust APIs and services to deliver real-time or batch recommendations (using Python, Go). This is a hands-on, cross-functional role ideal for someone who thrives at the intersection of Machine Learning, AI Engineering, and Business Impact.

Requirements

5+ years of experience in machine learning and backend software engineering
Proficiency in at least one backend programming language (e.g., Go, Java) and Python
Deep understanding of user modeling, embeddings, similarity search and ranking models
Strong experience with serving architectures (e.g., REST/gRPC APIs, model servers)
Experience with ML pipeline tools (e.g., MLflow, Kubeflow, Airflow)
Strong grasp of distributed systems, microservices, and system design
Experience with SQL and NoSQL databases and working with large-scale datasets
Exposure to experimentation platforms and online A/B testing.
Back-End Development
Machine Learning (ML)
Python (Programming Language)
Structured Programming

Responsibilities

Design and deploy intelligent, personalized recommendation models to drive user engagement.
Contribute to architecture, design, and implementation to deliver high quality AI driven solutions.
Design, build and maintain scalable ML infrastructure and production systems.
Collaborate with Data Scientists to architect data pipelines for serving and training ML models.
Lead the team to build scalable, low-latency, and fault-tolerant systems to serve real-time recommendations at scale.
Develop robust APIs and services to deliver real-time or batch recommendations (using Python, Go).