MLOps Engineer (Generative AI)
Tasks
- Collect metrics and create alerts
- Conduct feasibility studies
- Contribute to system architecture designs
- Create near real time AI ML responses
- Design and implement deployment pipelines
- Design and implement training pipelines
- Design monitoring dashboards
- Develop technical documentation
- Execute performance tests
- Execute unit tests
- Maintain scalable AI ML processing code
- Troubleshoot data and application issues
Perks/Benefits
Skills/Tech-stack
Agentic pipelines | Agile | Amazon Web Services | Azure | Azure Machine Learning | CI/CD | Cloud platform | Confluence | Distributed Systems | Docker | Git | Google Cloud | Google Cloud Platform | Grafana | Jira | Kanban | Kubernetes | Kubernetes Orchestrator | Linux | Machine Learning | ONNX | ONNX Runtime | Object-Oriented | Object-oriented programming | PyTorch | Python | Scrum | TensorFlow | Unit Testing | Web Services
Education
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