MLOps Engineer
Tasks
- Collaborate with data scientists and engineers
- Deploy ML models to production
- Design and maintain ML pipelines
- Develop and maintain CI/CD processes
- Implement data security and model governance
- Maintain documentation of processes and infrastructure
- Manage cloud and on-prem infrastructure
- Manage machine learning lifecycle
- Monitor deployed models and implement automated alerts
- Stay updated with MLOps technologies
Perks/Benefits
- Collaborative team
- Flexible work arrangements
- Impactful work environment
- Professional development
- State-of-the-art technology
Skills/Tech-stack
Cloud Platforms | Data Engineering | Docker | ELK Stack | Git | Go | Grafana | IT Infrastructure | Kubernetes | Lifecycle Management | ML Lifecycle | ML Lifecycle Management | Prometheus | PyTorch | Python | Rust | Scikit-learn | TensorFlow
Education
Roles
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