Adit Agarwal

Software Engineer

Bellevue, Washington, United States5 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Machine Learning and AWS technologies.
Proven track record in enhancing e-commerce logistics.
Strong background in deep learning applications.

Stackforce AI infers this person is a Machine Learning Engineer with a strong focus on E-commerce and Defense sectors.

Contact

aditagarwal1997@gmail.com LinkedIn

Skills

Core Skills

Project ManagementAwsMachine LearningJavaDeep LearningPython

Other Skills

AWS SageMakerAlgorithmsAmazon Web Services (AWS)BashC++Cascading Style Sheets (CSS)Data StructuresDjangoGNU OctaveHTMLKerasMatlabMeridianOpenCVProject Planning

About

Github Username: AditAg Codeforces Handle: aditagarwal

Experience

Amazon

4 roles

SDE II

Feb 2024 – Present · 2 yrs 1 mo

Working with Global Mile PAN and Pricing teams to help expand Amazon Global Logistics to EU28 countries.
Worked on the PAN charter where I worked on revamping an existing UI for EU sellers to store their inventory and change FBA settings.
Currently working with Pricing team which manages the quotation and pricing aspects for Global Logistics (GL) sellers with the end goal to enhance the experience provided to sellers when booking transporation through Amazon Global Logistics.

Project ManagementSoftware Development Life Cycle (SDLC)AWS SageMakerAmazon Web Services (AWS)AWS

SDE II

Promoted

May 2023 – Jan 2024 · 8 mos

Working with UFC (Universal Feature Catalog) Precompute team as part of the Classification and Policy Platform organization to build a platform for Applied Machine Learning teams at Amazon. This platform provides scientists capabilities to host their models, perform featurization (through multiple vending patterns) and precompute features and store them for consumption by consumers across Amazon. UIFC also manages the lifecycle of models and features.

Project ManagementSoftware Development Life Cycle (SDLC)AWS SageMakerAmazon Web Services (AWS)Machine LearningAWS

SDE II

Dec 2021 – Apr 2023 · 1 yr 4 mos

I worked with the Accounts Receivable team as part of the Global Mile organization which was responsible for managing the payments for shippers and sellers transporting their goods using Amazon cargo through the Global Mile program. Our team worked on enhancing the capabilities for sellers by supporting air shipments as well as small parcel shipments while enabling automated financial revenue recognition.

Project PlanningJavaAmazon Web Services (AWS)React.jsMeridianProject Management

SDE I

Jul 2020 – Nov 2021 · 1 yr 4 mos

Technische universität darmstadt

Summer Internship/M.Tech. Thesis

May 2019 – Jul 2019 · 2 mos · Darmstadt Area, Germany

Worked under Prof. Anirban Mukhopadhyay at the Medical and Environmental Computing (MEC) Lab, TU Darmstadt as a DAAD Fellow, on "Combining Information and Graph Theory to understand interpretability in supervised classification"

Amazon development centre (india) private limited

Summer Internship

May 2018 – Jul 2018 · 2 mos · Hyderabad Area, India

Worked as a SDE-I Intern in the Amazon Business Team at Amazon Development Centre Hyderabad. My work during the internship was "Making POOM and POSR configurable for Punchout customers". I also worked on Elastic Search and various code coverage tools.
Exposure: Java, DynamoDB

Defence research and development organisation

Summer Intern

May 2017 – Jul 2017 · 2 mos · New Delhi Area, India

Worked under Prof. Saibal Pal at DRDO (Defence Research and Development Organization) during summers 2017 in the field of Deep Learning and Cryptography.
Title: Cryptographic Applications of Deep Learning
Project: Implemented different deep learning architectures to improve the efficiency of cryptographic mechanisms as well as developed cryptographic schemes based on deep neural networks.
Also implemented papers to allow for deep learning architectures to run on resource-constrained embedded devices as well developed recurrent neural networks for binary data.
Implemented different deep learning architectures such as Hopfield Networks, Autoencoders, Boltzmann Machines, Restricted Boltzmann Machines(RBMs), Convolutional Neural Networks, Echo State Networks, LSTMs.
Also implemented recurrent neural networks for intrusion detection.
Technologies Used: Tensorflow, Keras libraries in Python