about 6 hours ago
Base Salary
$167k - $208k/yr
Responsibilities
- Build and operate the real-time inference service for model scoring.
- Own model deployment infrastructure including registry and CI/CD processes.
- Implement model observability features such as monitoring and drift detection.
- Collaborate with Risk Data Science for model handoff and production operation.
- Develop experimentation capabilities like champion/challenger and canary routing.
- Take responsibility for shaping and building a new platform team.
Requirements
- 5+ years in machine learning engineering, backend software engineering, or MLOps.
- Experience deploying and operating models in low-latency, high-availability contexts.
- Strong backend engineering skills in Python with API frameworks like FastAPI or Flask.
- Familiarity with model deployment and lifecycle tooling such as CI/CD and versioning.
- Experience building observability and alerting for production services.
- Comfort with SQL and low-latency data stores like Redis or DynamoDB.
Tech Stack
Amazon DynamoDBApache AirflowApache KafkadbtFastAPIFlaskHaskellPythonReactRedisSnowflakeSQLTypeScript