Senior Machine Learning Engineer
Remote · United States or US
Job Summary
Senior ML Engineer to own productionization and operational lifecycle of machine learning models from prototype handoff to production deployment, monitoring, and maintenance. Collaborate with Data Scientists to take validated models from notebooks to production systems serving predictions, build reusable tooling and self-service capabilities to enable faster iteration between Data Science and Production, containerize models with Docker, implement unit/integration tests, develop automated training pipelines (SageMaker Pipelines), build real-time and batch inference pipelines, integrate with Snowflake for feature retrieval and prediction storage, deploy to SageMaker endpoints, monitor performance and drift, and own incident response. Familiarity with Rails-based applications and API/webhook integrations, with a focus on scalable ML operations and cost optimization. 5+ years software experience, 3+ years ML systems, strong Python, AWS/SageMaker experience, Docker, data pipelines, Snowflake, and experience deploying ML models in production.
Required Qualifications
- 5+ years of software engineering experience
- 3+ years focused on ML systems
- Strong Python skills with emphasis on production code quality
- Experience deploying and operating ML models in production
- Hands-on experience with AWS (SageMaker preferred)
- Proficiency with Docker and containerization best practices
- Understanding of ML concepts to work with Data Scientists
- Experience building data pipelines and working with data warehouses (Snowflake a plus)
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