Tasks:
- * Build model lifecycle workflows
- * Build monitoring and alerting
- * Build task runtime and resource management
- * Coordinate cross-team integration and acceptance
- * Deliver offline and private deployments
- * Design platform architecture and APIs
- * Develop console and backend services
- * Establish release and rollback mechanisms
- * Implement scheduling and resource isolation
- * Integrate post-training pipelines
- * Lead engineering team and project delivery
- * Manage platform performance and reliability
Perks/Benefits:
Skills/Tech stack required:
[API Design] [Automated testing] [CI/CD] [Database Design] [Distributed Systems] [Docker] [Go] [GPU scheduling] [Java] [JavaScript] [Kubernetes] [Linux] [MLOps] [Model Registry] [Model Serving] [Model Training] [Object storage] [Observability] [Python] [React] [Resource Management] [Task Orchestration] [TypeScript] [Vue]
Educational requirements:
N/A
Role(s):
[AI Platform Engineering] [AI Platform Engineering Lead] [Engineer] [Engineering Lead] [Full-stack Software Engineer] [Lead] [Machine Learning Platform Engineer] [MLOps Engineer] [Platform Engineer] [Platform Engineering Lead] [Software Engineer]