- Lead and participate in research to build a large-scale synthetic data generation pipeline and orchestration solution.
- Optimize the performance, cost, and resource utilization of AI inference workloads using compute and memory optimization techniques.
- Contribute to open-source libraries for synthetic data generation and distributed reinforcement learning frameworks.
- Publish research in top-tier AI conferences such as ICML and NeurIPS.
- Write approachable technical blogs explaining project outcomes to customers and developers.
- Track advances in AI/ML infrastructure, tools, and synthetic data generation research, and identify opportunities to improve the platform.
CI/CDMLOps