Senior MLOps Engineer
Tasks
- Design ML platform
- Develop internal tools and APIs
- Implement CI/CD pipelines
- Improve training pipelines
- Integrate with runtime inference layer
- Manage model lifecycle
- Monitor model latency
- Monitor online and offline performance
- Operate ML workflows
- Perform data feature parity checks
- Support distributed GPU training
- Validate models before promotion
Perks/Benefits
Skills/Tech-stack
API Development | Airflow | Apache Spark | Asset bundles | CI/CD | Dagster | Data Validation | Databricks | Databricks (asset) | Databricks Asset Bundles | Delta Lake | Distributed Computing | Docker | FastAPI | Flask | GPU Training | GitHub | GitHub Actions | Kubernetes | MLflow | Model Deployment | Model Monitoring | Model Packaging | ONNX | ONNX Runtime | PyTorch | Pydantic | Python | Real Time | Real-time Inference | Unity Catalog
Education
N/A
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