Senior Machine Learning Operations Engineer
Tasks
- Alert teams when models degrade
- Automate statistical model validation prior to deployment
- Build ML platform components including feature store and model registry
- Contribute to service level objectives observability and on call operations
- Define workflows standards and KPIs for MLOps function
- Drive cost and latency improvements through architecture and model optimization
- Ensure reliability and performance of production machine learning systems
- Implement ML specific CI CD pipelines with data quality checks
- Implement data drift monitoring and concept drift monitoring
- Transition deployment process from manual notebook handoffs to PR driven workflows
Perks/Benefits
Skills/Tech-stack
AWS | Amazon S3 | Amazon SageMaker | Apache Airflow | CI/CD | Datadog | Feature Store | Incident Response | Infrastructure as Code | Kubernetes | MLOps | Machine Learning | Model Registry | Observability | Python | Snowflake | Terraform | “as-code”
Education
N/A
Regions
Countries
States
Cities
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