Data Engineer / MLOps and AI Engineer
Location: Mississauga, Canada
CAD 115K-151K (estimate) Mid-level Full Time
Tasks
- Apply secrets management role based access control and network policies
- Build model lifecycle pipelines
- Build validation pipelines with quality gates
- Coordinate releases and manage rollback strategies
- Create anomaly detection and hypothesis generation agents
- Create testing frameworks for ML and agent code
- Define feature sets lineage and reuse
- Design agent workflows on Cortex AI
- Design prompt architecture and agent instructions
- Develop batch and streaming data workflows
- Enforce HIPAA and GDPR compliance
- Establish contract integration and type checking tests
- Implement data protection for agents
- Implement logging tracing and alerting
- Implement model agent and data governance
- Maintain documentation operational playbooks and runbooks
- Manage version control approvals documentation audit trails
- Monitor data quality
- Optimize token economics and cost for agent execution
- Set up model performance and data drift monitoring
Perks/Benefits
Skills/Tech-stack
21 CFR | 21 CFR Part 11 | Access Control | Airflow | Alerting | Azure DevOps | CFR Part 11 | CI/CD | Cortex AI | Data Drift | Data Governance | Data Quality | Databricks MLFlow | Docker | Experiment tracking | GDPR | GitHub Actions | Go | HIPAA | JavaScript | LLM | Logging | Machine Learning | Model Monitoring | Model Packaging | Model Registry | Model Serving | Part 11 | Prompt engineering | Python | Role-Based Access | Role-Based Access Control | Rust | SOC2 | SQL | SageMaker | Secrets management | Snowflake | Snowpark | Spark | TDD | Token optimization | Tracing | TypeScript
Education
Roles
AI | AI Engineer | Data Engineer | Engineer | ML Engineer | MLOps Engineer
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