Chief Engineer
AUD 60K-200K (estimate) Executive-level Full Time
Tasks
- Automate data lifecycle tooling
- Deploy and monitor machine learning solutions
- Design and build enterprise data platform
- Develop DevSecOps practices
- Develop real time batch data ingestion and processing
- Ensure platform reliability and resilience
- Implement CI/CD pipelines for ML deployment
- Implement observability and monitoring
- Implement streaming data platforms
- Maintain platform documentation
- Provide technical leadership for data platform engineering
Perks/Benefits
- N/A
Skills/Tech-stack
AWS CloudFormation | AWS Glue | AWS IAM | AWS Lambda | AWS Step Functions | Amazon CloudWatch | Amazon DynamoDB | Amazon EC2 | Amazon ECS | Amazon EMR | Amazon RDS | Amazon Route 53 | Amazon S3 | Amazon SageMaker | Amazon VPC | Amazon Web Services | Apache Airflow | Artifactory | Bash | Batch Processing | CI/CD | Data Preprocessing | Data Processing | DevSecOps | Docker | Event Driven | Event-driven architecture | Feature Engineering | GitHub | GitHub Actions | Grafana | Infrastructure as Code | ML Lifecycle | Machine Learning | Model Deployment | Model Evaluation | Model Training | Prometheus | Python | Real Time | Real-time Data | Real-time Data Processing | Route 53 | Snowflake | Snyk | Step Functions | Streaming Analytics | Web Services | “as-code”
Education
N/A
Roles
Chief | Chief Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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