Tayo Oguntebi
Member Of Technical Staff at Microsoft AI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTayo Oguntebi is a systems architect and software engineer with 11+ years building high-performance ML infrastructure and compiler backends, now a Member of Technical Staff at Microsoft AI after a decade leading efficiency work at Google. He specializes in hardware/software tradeoffs across TPUs, GPUs, and heterogeneous datacenter environments, with hands-on contributions to XLA and TensorBoard and a winning MLPerf recommender submission that outperformed major vendors. His background spans from silicon and hardware acceleration (Intel, NVIDIA, FPGA co‑processors) to co-founding a quantum SaaS startup, giving him rare end-to-end fluency from chip to model. Passionate about applying technology to education and healthcare, he focuses on cost-effective model and data optimizations that enable larger, more capable systems.
11 years of coding experience
18 years of employment as a software developer
Bachelor of Science (BS), Computer Engineering, Bachelor of Science (BS), Computer Engineering at Georgia Institute of TechnologyMaster of Science (MS), Electrical Engineering, Master of Science (MS), Electrical Engineering at Stanford University
French
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (21)
c-language10
operation10
python10
machine-learning10
tpu10
keras10
deep-learning10
tensorflow10
performance-optimization10
hla10
xla10
compiler10
cprogramming-language10
javascript9
recommendation-system9
Programming languages (7)
Github contributions (5)
openxla/xla
Jan 2017 - Jun 2022
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:
Back-end Developer
Back-end DeveloperContributions:30 commits in 5 years 5 months
Contributions summary:Tayo primarily contributed to the XLA compiler, focusing on adding and modifying HLO (High-Level Operations) within the codebase. Their work involved implementing a new "Outfeed" HLO operation, which handles the output of data, and making associated changes across multiple files, including `hlo_instruction.cc`, `computation_builder.h`, `user_computation.cc`, and `hlo_instruction.h`. The user's contributions also include support for generic reduction functions in ReduceWindow and enhancements related to ReduceWindow tests.
compilercommunity-drivenmachine-learningmodular
tensorflow/tensorboard
Sep 2017 - Oct 2020
TensorFlow's Visualization Toolkit
Role in this project:Back-end Developer
Back-end DeveloperContributions:14 commits, 15 PRs, 12 comments in 3 years 1 month
Contributions summary:Tayo primarily focused on updating and maintaining the whitelist of TPU-compatible operations within the TensorFlow TensorBoard project. Their contributions involved identifying and incorporating new TensorFlow operations that are compatible with TPUs, as well as removing deprecated ones. They made multiple updates to `op.ts`, ensuring the graph visualization tool accurately reflects the latest TPU compatibility status. This work improved the accuracy and functionality of the TensorBoard graph visualization tool for TPU-accelerated models.
machine-learningtensorflowvisualization
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