Computer Vision Software Engineer2019 - 2021
Technologies: C++, Python, PyTorch
- Debugged and configured a production image inference system in C++ that processes thousands of queries per second. Solved a problem that negatively impacted accuracy for all image models and proactively caught a subtle use-after-free bug.
- Contributed research directions and code to GrokNet, a model for fine-grained image recognition across several business verticals, including developing a novel way to aggregate contrastive loss pairs across GPUs.
- Co-developed SimSearchNet++, a model for near-duplicate image detection.
Software Engineer2018 - 2019GrokStyle
Technologies: C++, Python, PyTorch, Django, Amazon Web Services (AWS), Google Cloud
- Improved throughput of image loading by over eight times to support multi-GPU training.
- Led migration of the core training and inference stack from Caffe to PyTorch.
- Cut search cost and latency by four times by finding and implementing optimization opportunities in a core search routine, including replacing a previous BLAS-accelerated implementation with a custom C++ implementation.
Software Engineering Intern2017 - 2017
Technologies: C++, Image Processing
- Ported an image super-resolution algorithm to run on custom coprocessors.
- Leveraged symmetries to fit large lookup tables into 16KB of on-chip memory.
- Wrote a fixed-point square root approximation which achieved a two-time speedup.