ML Engineer
Tasks
- Architect data and compute infrastructure
- Automate end-to-end machine learning pipeline
- Build MLOps foundations
- Build inference systems APIs batch processing and streaming
- Deploy and monitor machine learning models
- Design production machine learning systems
- Develop feature engineering workflows
- Implement model governance and reproducibility
- Optimize resource usage and performance bottlenecks
Perks/Benefits
- N/A
Skills/Tech-stack
AKS | Apache Airflow | Apache Spark | Azure | Batch Processing | Data Pipelines | Databricks | Deep learning | Feature Engineering | GPU Acceleration | Inference APIs | Kubernetes | MLOps | MLflow | Machine Learning | Model Evaluation | Model Monitoring | Python | R | Real Time | Real-time Streaming | Statistical Analysis
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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