Senior Machine Learning Operations Engineer

Who We Are 

Hungryroot is the only grocery and recipe delivery service designed to make healthy eating simple, personal, and sustainable. Our mission is to help people feel their best by making it easier to shop for, cook and love healthy foods. By leveraging AI to create a truly personalized experience, we save customers time and worry, all while introducing them to new foods and helping them achieve their health objectives. 

People are at the center of everything we do here at Hungryroot. We are a remote-first company with a hub office in NYC. It’s up to you how and where you want to work; we care about outcomes and your contribution to our company. Our work, our decisions, and our culture are deeply-rooted in the values of being positive, proactive, and transparent. We’re incredibly proud of our team and hope that you’ll join us!

About the Role

We’re looking for a Senior Machine Learning Operations Engineer to be a part of our growing Data Science team. You’ll be responsible for building and maintaining the infrastructure and tools necessary to support the deployment, monitoring, and management of our Operations Research (Spark, Gurobi) and Machine Learning models (Spark, Python, Scala and C++ libraries). They will collaborate closely with cross-functional teams, including data scientists, data engineers, and DevOps, to ensure the seamless integration of Operations Research and Machine Learning solutions into our production and staging environments.

This role will join Hungryroot’s Data Science team and you’ll report directly to our VP of Data Science. In this critical role you will work closely with our data scientists and operation research experts to tackle the core challenges at the company that will be crucial to the success of Hungryroot. If you want to help us change how people grocery shop and eat for the better, we’d love for you to apply!

Responsibilities

• Develop, implement, and manage scalable operations research and machine learning pipelines for data preprocessing, model training, validation, and deployment on Databricks and Gurobi Cloud using Terraform.

• Collaborate with data scientists and software engineers to deploy machine learning models into production and optimize their performance for real-world scenarios.

• Establish monitoring and alerting systems to ensure the health, availability, and accuracy of deployed models, utilizing tools like Datadog, and custom monitoring scripts.

• Work closely with the DevOps team to automate and streamline the deployment and management of machine learning systems.

• Continuously improve the ML Ops processes by identifying bottlenecks, implementing best practices, and staying up-to-date with the latest advancements in the field.

Requirements

• Minimum 3 years of experience in an Machine Learning Operations, DevOps or related track

• Minimum 2 years of ML Ops experience with Databricks

• CI/CD Experience

• Proficient with Terraform

• AWS Networking experience

• Pipeline scheduling with Airflow

• Monitoring and alerting with Datadog

• Basic Experience with Python and Scala

Perks and Benefits

• Remote-first: work from home, work from our NYC office, work from anywhere in the US. You decide!

• Equity stake

• Unlimited vacation policy

• Universal paid parental leave

• Monthly Hungryroot credit for delicious, healthy groceries

• Comprehensive health, vision, dental, and life insurance

• Wellbeing benefits including One Medical, Spring Health, LiveHealth, Rightway care concierge, and more

• 401k

• A WFH stipend to support your initial home-office setup

#LI-REMOTE

Hungryroot is built on the values of being proactive, positive, and transparent in all that we do. Our mission to help make healthy eating easy, accessible, and joyful is better served by a diverse workplace. 

We are a proud Equal Opportunity Employer committed to building an inclusive workplace. We have zero-tolerance for harassment or discrimination. We do not discriminate on the basis of race, religion, ethnicity, national origin, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or disability.