Software Engineer II - MLOps
Tasks
- Build automated end to end machine learning pipelines
- Deploy machine learning models to production
- Develop continuous deployment pipelines
- Develop continuous integration pipelines
- Document technical processes and operational procedures
- Establish system reliability solutions
- Evaluate emerging technologies
- Implement continuous evaluation for models
- Implement feature engineering pipelines
- Implement monitoring, logging, and alerting
- Monitor machine learning models in live environments
- Operationalize machine learning models for production readiness
- Optimize system architecture for scalability uptime and cost
Perks/Benefits
Skills/Tech-stack
Alerting | Apache Airflow | Apache Kafka | Apache Spark | Continuous Deployment | Continuous integration | Data Pipelines | Distributed Systems | Feature Engineering | Logging | MLOps | Machine Learning | Model Monitoring | Python
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Roles
Engineer | Engineer II | MLOps Engineer | Software Engineer | Software Engineer II
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