---
title: "Deepak Prasad - Software Engineer 2 (L62) in Bengaluru | Tal"
description: "Meet Deepak Prasad, SDE 2 @ Microsoft | Ex - Amazon | Ex - McAfee based in Bengaluru. AI stack includes claude, github copilot, and mcp."
image: "https://tal.club/meet/deepak-prasad-2/share-image"
---

# Deepak Prasad on Tal

## Headline

SDE 2 @ Microsoft \| Ex \- Amazon \| Ex \- McAfee

## Location

Bengaluru

## AI stack

claude

github copilot

mcp

openai

githubcopilot

## Work experience

Software Engineer 2 \(L62\) at Microsoft, Feb 2025 \- Present · 1 yr 8 mos, Hyderabad, Telangana, India

Software Development Engineer 2 at Amazon, Jul 2024 \- Feb 2025 · 8 mos, Delhi, India

Software Development Engineer at Amazon, Jun 2022 \- Jun 2024 · 2 yrs 1 mo, Bengaluru, Karnataka, India

Software Development Engineer at McAfee, Aug 2020 \- Jun 2022 · 1 yr 11 mos, Bengaluru, Karnataka, India

Undergraduate Technical Intern at McAfee, Feb 2020 \- Aug 2020 · 7 mos, Bangalore, India

Summer Research Intern at Ryerson University Research and Innovation, May 2019 \- Aug 2019 · 4 mos, Toronto, ON, Canada, We worked on Screening and analysis of specific language impairment in young children by analyzing the textures of the speech signals\. We published the paper at the 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society \(EMBC\)\. As 2nd author, my contribution was processing the audio data, remodeling, and applying various machine learning models to develop a system to screen specific language impairment in young children\. We were successful in developing a model with 98% accuracy\.

Machine Learning Intern at Indian Institute of Technology \(Banaras Hindu University\), Varanasi, Jun 2018 \- Jul 2018 · 2 mos, Varanasi, Uttar Pradesh, India, We had hands\-on experience with the use of machine learning models with IoT devices\. We generated datasets using Raspberry Pi, Pre\-processed the Datasets using outlier detection, Normalization, Binarization, Data cleaning, etc\., applied different machine\-learning algorithms like liner regression, logistic regression, neural network, SVM, Decision Tree, and K\-NN classification \(using various distance metrics\), estimated the quality of predictions using various model evaluation metrics\.

## Education

Bachelor of Technology, Computer science and engineering, National Institute Of Technology Sikkim

[View the original profile](https://tal.club/meet/deepak-prasad-2)

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