Build and maintain ML infrastructure, pipelines, and serving systems to enable scalable model training, evaluation, and inference with observability and reliability.
- Build ML infrastructure
- Build evaluation and benchmarking infrastructure
- Create data preparation and training pipelines
- Deploy and operate model inference services
- Design model training and evaluation systems
- Develop model serving and inference infrastructure
- Enable faster experimentation with ML tooling
- Implement production observability monitoring tracing alerting
- Improve reliability scalability latency throughput and cost