Software Engineer ( Machine Learning Ops )
Tasks
- Automate model training testing deployment
- Collaborate with data scientists operationalize models
- Deploy models in pre prod and prod environments
- Design ML pipelines for training validation deployment
- Implement version control for models datasets and experiments
- Maintain documentation for ML workflows and system architecture
- Monitor model performance data drift and system health
- Optimize ML infrastructure for scalability reliability cost
- Troubleshoot model deployment and production issues
Perks/Benefits
Skills/Tech-stack
AWS | Apache Airflow | Azure | CI/CD | Docker | Feature Store | GCP | Git | Grafana | Infrastructure as Code | Kafka | Kubernetes | Logging | ML Systems | MLflow | Model Explainability | Monitoring | Prometheus | PyTorch | Python | SQL | Scikit-learn | TensorFlow | “as-code”
Education
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