Staff Machine Learning Engineer
Tasks
- Build automated machine learning pipelines
- Deploy and operate machine learning models in production
- Design backend architecture for model serving APIs
- Develop well documented secure and reliable machine learning APIs
- Ensure scalability reliability latency observability and security
- Establish model governance with experiment tracking and dataset versioning
- Evaluate emerging machine learning tooling and technologies
- Lead machine learning engineering team
- Manage model lifecycle including monitoring versioning validation rollback and retirement
- Mentor engineers and conduct technical reviews
- Productionize validated research outcomes
- Set engineering standards and drive continuous improvement
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | Azure ML | CI/CD | Cloud Computing | Dataset Lineage | Dataset versioning | Distributed Systems | Docker | Drift Detection | Experiment tracking | Feature Stores | GPU Inference | Google Cloud | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Microservices | Model Deployment | Model Governance | Model Monitoring | Model Registry | Model Rollback | Model versioning | ONNX Runtime | OpenVINO | RESTful APIs | SageMaker | Scalable architectures | TensorRT | Vertex AI
Education
Regions
Countries
States
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