Senior ML Ops Engineer (Machine Learning Infrastructure)
Tasks
- Architect ML infrastructure for distributed training and inference
- Automate model evaluation selection and deployment
- Build cloud ML systems for R and D and production
- Deploy and monitor models
- Design MLOps pipelines for data management
- Implement continuous integration deployment for ML workflows
- Integrate ML tools for experiment tracking and workflow management
Perks/Benefits
Skills/Tech-stack
Amazon SageMaker | Apache Airflow | CI/CD | Computer Vision | Data Ingestion | Distributed Training | Git | Horovod | Kubeflow | MLflow | Metaflow | Model Deployment | Model Evaluation | Model Packaging | Model Training | PyTorch | Python | Ray
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Cities
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