Build and maintain ML infrastructure, pipelines, and tooling for training, evaluation, and production deployment of AI models.
- Build ML infrastructure platforms
- Build data preparation training evaluation pipelines
- Build experimentation tooling for ML teams
- Create evaluation benchmarking and regression detection
- Deploy machine learning models to production
- Design model training and evaluation systems
- Implement observability monitoring tracing alerting
- Improve reliability scalability latency throughput cost
- Operate inference and model serving systems
- Optimize distributed systems performance