Sr ML & AI Engineer
Tasks
- Automate testing and model packaging
- Build CI CD for machine learning
- Design machine learning pipelines
- Detect model degradation and latency issues
- Develop monitoring and observability
- Develop scalable model serving architectures
- Ensure model reproducibility and rollback
- Evaluate MLOps platforms and tooling
- Implement data drift detection
- Implement model and data versioning
- Implement model deployment workflows
- Maintain containerized training environments
- Orchestrate machine learning workloads
- Support human-in-the-loop workflows
Perks/Benefits
Skills/Tech-stack
AWS | Apache Airflow | Azure | Batch inference | CI/CD | Containerization | DVC | Data Drift | Data Drift Detection | Data Versioning | Distributed Computing | Docker | Drift Detection | Google Cloud | Infrastructure as Code | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Model Monitoring | Model Serving | Model Validation | Observability | Python | Real Time | Real-time Inference | Retraining | Spark | Streaming Architecture | Version control | Workflow Orchestration | “as-code”
Education
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