Navya Mehta
Principal Engineer And Technical Lead - Compiler Engineering at EnCharge AI
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolNavya Mehta is an early-stage ML compiler engineer with 7 years of experience building high-performance systems spanning edge AI, backend infrastructure, and production ML. Currently an early software-side hire at EnCharge AI, she focuses on compiler infrastructure, quantization, and end-to-end simulation for a >150 TOPs/W edge chip. Previously a founding engineer at WOMBO.ai, she scaled async queuing, custom schedulers, and a <100ms vector-embedding semantic search to support 50M+ downloads and 1M DAU, blending low-latency systems engineering with ML deployment. Her background includes MLIR and C++ compiler work at Groq, ultra-low-latency trading systems at Jane Street, and data-driven modeling across finance and retail, showing a rare mix of algorithmic rigor and product impact. A Waterloo CS + Finance graduate and former research assistant in statistical optimization, she brings both theoretical depth and practical chops in optimization, memory-locality, and instruction compression. Notably, she has shipped novel compiler rewriters and graph-folding techniques that materially reduced IR size and instruction count on real-world networks.
7 years of coding experience
3 years of employment as a software developer
High School GPA: 3.99/4.00; IB World Topper: 45/45, High School GPA: 3.99/4.00; IB World Topper: 45/45 at Dhirubhai Ambani International SchoolBachelors of Honours Computer Science + Finance (Minor: Statistics), Bachelors of Honours Computer Science + Finance (Minor: Statistics) at University of Waterloo
English, French, Gujarati
Github Skills (96)
fastapi10
python10
json-schema10
swagger10
asgi10
async10
django10
mypy10
api10
rest10
json10
graphql-schema10
type-annotations10
graphql10
starlette9
Programming languages (6)
Github contributions (5)
navyamehta/jane-street-electronic-trading-comp
Jun 2019 - Jun 2020
Contributions:33 commits, 33 pushes, 1 branch in 1 year
navyamehta/dividend-forecast-simulation
Jun 2019 - Aug 2019
We attempt to build predictive ML models to help investors create dividend forecasts for S&P500 companies. By building a proprietary data pipeline, we perform data preprocessing, cleaning and feature engineering on historic financial data to derive market insights.
Contributions:121 commits, 122 pushes, 1 branch in 1 month
data-pipelinedata-preprocessingfeature-engineeringmlmodel
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