Senior MLOps Engineer — Remote, Equity, Unlimited PTO

United States Digital Space LLC; United States; Remote; USD 170,000 - 210,000; Full time

Benefits offered by this job

Remote-first

Equity

Unlimited vacation

Parental leave

Hungryroot credit

Health insurance

401k with company match

Home-office stipend

Job summary

Hungryroot is hiring a Senior Machine Learning Operations Engineer to join our Data Science team. Our platform runs Python services, FastAPI on AWS, Spark pipelines on Databricks, and real-time ML-driven personalization.

You’ll partner with data scientists and product engineers to scale model-driven decisions. This role focuses on production ML infrastructure, MLflow lifecycle, CI/CD, IaC, and observability to ensure reliable, low-latency systems that power recommendations and grocery

Qualifications

• 5+ years in MLOps, ML engineering, or DevOps with production ML infra.
• Strong Python and SQL; Bash for automation.
• Experience designing and operating backend services and APIs (e.g., FastAPI) with reliability, latency, and scalability.
• Hands-on with Databricks and Spark and MLflow or similar lifecycle tooling.
• Experience building CI/CD for ML/data systems and IaC (GitHub Actions/Jenkins, Terraform).
• Solid AWS fundamentals: IAM, networking, compute/cluster management, Docker, ECS/EKS.
• Production observability: metrics, logging, alerting, data quality, and drift.

Responsibilities

• Design, build, and operate scalable backend services, APIs, and data pipelines.
• Improve 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 interfaces for new ML models and decisioning capabilities, including experimentation and feature-flag tooling.
• Strengthen engineering foundations across a growing codebase: automated testing, type checking, CI/CD, IaC, documentation, and thoughtful system design.
• Profile data-heavy services and pipelines; reduce execution time and memory footprint where it matters.
• Collaborate with data scientists, operations researchers, and product engineers to translate business needs into robust technical solutions.

Skills

MLOps

Python

SQL

Databricks

CI/CD

AWS

Observability

Tools

Databricks

Spark

MLflow

Terraform

GitHub Actions

Jenkins

Docker

ECS/EKS

Job description

Hungryroot is hiring a Senior Machine Learning Operations Engineer to join our Data Science team. Our platform runs Python services, FastAPI on AWS, Spark pipelines on Databricks, and real-time ML-driven personalization.

You’ll partner with data scientists and product engineers to scale model-driven decisions. This role focuses on production ML infrastructure, MLflow lifecycle, CI/CD, IaC, and observability to ensure reliable, low-latency systems that power recommendations and grocery