Quick Responder

Navya Mehta

Tech Lead - Core ML Compilers @ EnCharge AI
5.0
(1 review)
4+ years building early-stage ML inference and compiler systems. Ex-Groq, Jane Street, Splunk
Canada Active last week Usually responds in half a day

Services

$200 / month

Love to talk with engineers to build a deeply technical skillset in big tech, early startups etc.

2 calls per month (60min/call)

Unlimited Q&A via chat

Expect responses in 24 hours or less

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About

I love building 0-1 products to tackle deeply technical problems to hope to have an outsized impact on the world.

I'm an early-stage engineer (Series A) at EnCharge AI, building the compiler (mapping, placement, allocation, scheduling) stack for a novel analog-based edge chip. My work spans building new hardware-aware placement/scheduling algorithms for our chips, researching new defragmentation and memory allocation heuristics, leading numerical stability experimentation to ship quantized models, and more.

I was a founding engineer at WOMBO AI, helping build the company for over 2 years. I've built large scale machine learning inference projects for > 3 billion inferences, designed <100ns semantic search-driven content recommendation systems, and scaled our backend to > 3 million daily users.

I've previous worked at Jane Street, Groq, Splunk, and BMO Capital Markets, across low-latency trading systems, compilers for custom hardware, rapid prototyping systems for security apps, and more.

What mentees say

5 out of 5 stars

I had an opportunity to speak with Navya about the various career options available to me at this stage of my career. Navya introduced me to ML Compilers and explained how they fit within AI systems, using excellent examples that further sparked my interest in the field. It was a fantastic session which was super worth of time, and I look forward to speaking with him more and seeking his guidance as I learn further.

Karthikeyan

Karthikeyan

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