MLOps Team Lead
Tasks
- Build and maintain data pipelines
- Build internal machine learning platform
- Collaborate with R and D to translate research needs
- Design end to end infrastructure and pipeline initiatives
- Develop automation for research workflows
- Ensure data accuracy, consistency, and efficiency
- Lead and mentor MLops engineers
- Migrate platform components from Dask to Ray
- Own ML model lifecycle
- Run pipelines to production
- Set engineering standards through code reviews and guidance
- Train deploy monitor and retrain models
Perks/Benefits
- N/A
Skills/Tech-stack
Amazon Web Services | Apache Airflow | Apache Spark | CI/CD | Cloud platform | Dagster | Dask | Data Pipelines | Distributed Computing | Docker | Google Cloud | Google Cloud Platform | Inference Pipelines | Kubernetes | MLOps | Machine Learning | Microsoft Azure | Model Monitoring | Python | Ray | Training pipelines | Web Services
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Engineer | Engineer | Lead | Learning Engineer | ML Ops Team Lead | MLOps Engineer | Machine Learning Engineer | Team Lead
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