Hiring: Senior Machine Learning Operations Engineer Company: Hungryroot Location: United States Job Posted Time: 2026-09-16 18:37:30 Employment Type: Remote Target Skills & Keywords : AWS, Bash, C++, CI/CD, Data Pipeline, Databricks, Docker, ECS, EKS, FastAPI, Feature Store, Git, GitHub Actions, IAM, Infrastructure as Code, Jenkins, MLOps, MLflow, Machine Learning, Python, SQL, Scala, Spark, Systems Design, Terraform About the job Experience: •5+ years in MLOps, ML engineering, or DevOps with a focus on production ML infrastructure. Required Skills: •We’re hiring a Senior Machine Learning Operations Engineer to join Hungryroot’s Data Science team. Our team owns the production systems that power grocery recommendations and box personalization for Hungryroot customers. •Our platform combines Python services, FastAPI APIs running on AWS, Spark pipelines on Databricks, and machine learning models that feed a real-time decisioning engine. The system is actively evolving, and we’re investing in the engineering foundations that will let it scale and adapt with the business. •You’ll partner closely with data scientists, operations researchers, and product engineers to build reliable, extensible systems for model-driven personalization. This is an opportunity to shape the architecture behind a core part of Hungryroot’s customer experience. •Design, build, and operate scalable backend services, APIs, and data pipelines. •Improve the reliability, performance, and observability of production ML and optimization systems. •Own the path from trained model to production: model versioning and registry (MLflow), safe rollout and rollback, and monitoring for data quality and model drift. •Build clean interfaces that let new ML models and decisioning capabilities integrate safely and efficiently, including experimentation and feature-flag tooling. •Strengthen engineering foundations across a growing codebase: automated testing, type checking, CI/CD, infrastructure as code, documentation, and thoughtful system design. Qualifications: •Strong Python and SQL; Bash for automation and tooling. •Applied hands-on capability in Databricks and Spark (jobs/workflows, Unity Catalog a plus) and MLflow or comparable model lifecycle tooling (registry, versioning, experiment tracking). •Solid AWS fundamentals: IAM, networking, compute/cluster management, containerized workloads (Docker; ECS or EKS). •Operational familiarity with recommendation, personalization, or operations research systems — especially productionizing them. •Feature store experience (Databricks Feature Store, Feast, Tecton) serving consistent online/offline features. •Additional languages such as Scala or C++. Compensation: •$170,000 - $210,000 / year •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!