Machine Learning Operations Engineer
Tasks
- Build and optimize end-to-end ML pipelines
- Build monitoring logging and alerting for model health
- Design scalable infrastructure for production ML models
- Document technical standards operational procedures and architecture decisions
- Implement CI CD pipelines for ML releases
- Improve system architecture for scalability reliability uptime and cost
- Integrate emerging MLOps tools and best practices
- Operationalize ML models for production readiness
Perks/Benefits
- Experimentation learning and ownership culture
- Flexible working hours
- Home office setup support
- Inclusive environment
- Paid time off
- Remote-first work environment
- Setup stipend
Skills/Tech-stack
Alerting | Apache Airflow | Apache Spark | CI/CD | Cloud infrastructure | Continuous Evaluation | Distributed Systems | Kafka | Logging | MLOps | Machine Learning | Monitoring | Python | Workflow Orchestration
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
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