$ whoami

Snehith
Nayak

Software Engineer @ Applied Materials  ·  M.S. Applied Data Science @ University of Michigan

snehith — zsh
~$ cat profile.json
{
  "name": "Snehith Nayak",
  "role": "Software Engineer AIx",
  "company": "Applied Materials",
  "grad": "M.S. Applied Data Science",
  "school": "Univ. of Michigan",
  "location": "Bay Area, CA",
  "interests": ["ML", "Semiconductors", "Data"]
}
~$

Experience

July 2024 — Present
Software Engineer AIx
Applied Materials  ·  Santa Clara, CA
Python Machine Learning FastAPI ClickHouse AWS / S3
  • Solving problems that didnt exist a month ago
June 2023 — Sept 2023
Machine Learning Engineer Intern — BBP
KLA  ·  Milpitas, CA
Python TensorFlow Image Classification
  • Taught computers how to learn
June 2022 — Sept 2022
Application Development Intern
Synopsys  ·  Santa Clara, CA
SQL Python
  • Made data do things it probably didn't want to do
Jun 2018 — Jan 2021
Founder
NPTutoring
Python HTML/CSS/PHP Firebase
  • Taught students how to code

Education

Projects

Nov 2023 — Jun 2024

Health Monitoring Wearable — Capstone

Designed and manufactured a health monitoring wearable for nursing home residents: vital signs, activity tracking, temperature, ambient noise, and continuous heart rate/SpO₂. Built a 4-layer PCB in Altium and a data-efficient Android app for real-time visualization.

PythonCJavaASIC DesignAltium
Jan 2023

Chromatic Tuner FPGA Development

Engineered a precise guitar tuner (65–4500 Hz) on FPGA. Enhanced FFT code for sub-30ms results using optimized lookup tables and hash-maps. Built an interactive GUI on a QP-nano Hierarchical State Machine with rotary encoders and onboard buttons.

CC++FPGAEmbedded Systems
Personal Project

Stock Market Sentiment Analysis

Developed a predictive model using NLP sentiment analysis on news articles, crawling APIs to surface positive/negative market signals. Built a GUI dashboard for real-time visualization of sentiment scores.

PythonNLPML
Competition

Supply Chain Optimization

Ran regression analysis to optimize manufacturing output for a jeans company at a national competition. Modeled machine allocation, staffing, and throughput to maximize monthly revenue.

PythonRegressionOptimization
UCSB IEEE

Emotional Intelligence AI

Collaborated with 15 engineers at UCSB IEEE to develop a deep learning model capable of detecting up to 7 basic emotions from real-time webcam input using computer vision.

PythonDeep LearningComputer Vision

Skills

// Languages

Python C++ C SQL Java HTML / CSS

// ML / AI

PyTorch TensorFlow Deep Learning Computer Vision NLP

// Tools & Platforms

FastAPI ClickHouse AWS / S3 Firebase Git

// Hardware

FPGA ASIC Design PCB Design Embedded Systems Digital Logic