Senior Machine Learning Operations Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and manage scalable backend services, APIs, and data processing pipelines.

• Enhance the reliability, performance, and monitoring capabilities of production ML and optimization systems.

• Take ownership of the journey from trained model to production, including model versioning, registry management, secure rollout and rollback processes, and monitoring for data quality and model drift.

• Create interfaces for the safe integration of new ML models and decision-making capabilities, incorporating experimentation and feature-flag tooling.

• Fortify engineering foundations through automated testing, type checking, CI/CD practices, infrastructure as code, thorough documentation, and system design.

• Analyze data-intensive services and pipelines to minimize execution time and memory usage.

• Collaborate with data scientists, operations researchers, and product engineers to convert business requirements into technical solutions.

⛳️ Requirements

• Over 5 years of experience in MLOps, ML engineering, or DevOps with a focus on production ML infrastructure.

• Proficient in Python and SQL; Bash for automation and tooling tasks.

• Demonstrated experience in designing and managing reliable, low-latency, and scalable backend services and APIs, such as FastAPI.

• Practical experience with Databricks and Spark, including jobs and workflows; familiarity with Unity Catalog is advantageous.

• Experience with MLflow or similar model lifecycle tools for registry, versioning, and experiment tracking.

• Proven ability to establish CI/CD for ML or data systems using Git, GitHub Actions/Jenkins, or Databricks Asset Bundles.

• Experience in infrastructure as code utilizing Terraform or similar tools.

• Strong foundational knowledge of AWS services: IAM, networking, compute/cluster management, Docker, ECS or EKS.

• Experience with production observability, including metrics, logging, alerting, data quality monitoring, and model drift tracking.

• The employer is unable to sponsor applicants for work visas.

🏝️ Benefits

• Remote-first: choose to work from home, our NYC office, or anywhere else in the U.S. - the choice is yours!

• Equity opportunities.

• Unlimited vacation policy.

• Comprehensive paid parental leave.

• Monthly Hungryroot credit for delicious and healthy grocery options.

• Extensive health, vision, dental, and life insurance coverage.

• 401k plan with company matching contributions.

• A stipend to assist with your home-office setup.

• Annual company retreat.

• Regular virtual team events.