Implemented automatic model partitioning for multi-gpu inference; built this on top of a system created by our R&D team creating a Virtual Tensor abstraction that streamed PyTorch ops to remote workers. (Python)

Closely interfaced with open-source PyTorch 2.0 developments, filed issues, and contributed fixes. (Python)

Handled, ran, profiled, and debugged customer models and open-source models directly, in various frameworks including PyTorch, ONNXRuntime, TensorFlow, and TVM.

Drove model deployment and accuracy validation initiatives, both internally and for external hardware companies. (Python)

Significantly reduced model optimization strategy search time via design of a tuning records caching service. (Rust, Python)

Bootstrapped visualizations and frontend interactions, from scratch. (React, JS, vega)

Helped bootstrap the SaaS platform, from scratch. Defined database schemas, created APIs, defined protobufs, worked on all components of the whole e2e flow: client -> api server -> scheduler -> worker. (Rust)

Did a lot of random terraform.

Iterated through alternative prototypes to discover product-market fit.

Hacked on the TVM compiler -- improved coverage and added metadata passes. (C++)

Designed and created a weekly integration model testing service. (Python, Kubernetes)