AI/ML Platform Engineer
Tasks
- Automate platform support and operational readiness
- Build AI ML deployment pipelines
- Create reusable platform templates and automation
- Define platform architecture and engineering standards
- Design AI ML platform capabilities
- Develop model registry and experiment tracking
- Drive monitoring incident response and resiliency improvements
- Ensure reliability scalability security observability and cost optimization
- Implement multi tenancy and resource isolation
- Maintain operational runbooks and documentation
- Operate model lifecycle tooling
- Provide technical mentorship and guidance
Perks/Benefits
- Accessibility
- Cafeteria
- Childcare
- Coaching
- Employee discounts
- Employee events
- Flexible working hours
- Good Public Transit
- Health programs
- Mobility offers
- Parking
- Retirement plan
Skills/Tech-stack
CI/CD | Cloud | Delta Lake | Distributed Computing | Docker | Event Driven | Event-driven architecture | Experiment tracking | Feature Store | GPU Computing | Infrastructure as Code | Infrastructure automation | Kubernetes | Logging | MLOps | MLflow | Model Registry | Model Serving | Monitoring | Observability | PySpark | Python | SQL | Streaming | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Platform Engineer | Engineer | ML Platform Engineer | Platform Engineer
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