Arpit Singh

Co-Founder

India2 yrs 8 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Award-winning research in Federated Learning.
Developed robust microservices with 1000% performance optimization.
Built Android games showcasing strong programming skills.

Stackforce AI infers this person is a skilled software engineer with expertise in SaaS, EdTech, and Gaming industries.

Contact

arpit@getaida.com LinkedIn

Skills

Core Skills

Machine LearningFlaskSpring BootJavaDistributed SystemsFlutterGame Development

Other Skills

AlgorithmsAmazon EKSArtificial Intelligence (AI)Business OwnershipC (Programming Language)C#C++Competitive ProgrammingComputer ScienceComputer VisionDartData ScienceData StructuresHTMLJUnit

About

I am an engineering undergrad at Indian Institute of Technology Kanpur, majoring in computer science.

Experience

Aida

Founding software engineer

Jan 2025 – Present · 1 yr 2 mos

AIDA is the AI Chief of Staff built for revenue teams. We capture every commitment across email, CRM, calls, and Slack, surfacing the right next step, prepping reps with the context they need, and flagging risks before they derail your forecast.

Socia

_

May 2024 – Present · 1 yr 10 mos

Cohesity

Member of Technical Staff

Jul 2023 – Jan 2025 · 1 yr 6 mos · Bengaluru, Karnataka, India · On-site

Tessell

Member of Technical Staff

Feb 2023 – Jul 2023 · 5 mos · Bengaluru, Karnataka, India · Hybrid

Machine LearningFlaskSpring BootArtificial Intelligence (AI)Python (Programming Language)Java+1

American express

Technology Intern

May 2022 – Jul 2022 · 2 mos

Implemented robust and loosely coupled micro services and RESTful APIs in java using spring‑boot framework.
Optimized micro‑service performance by 1000% by leveraging parallel processing.
Implemented an automated data‑driven testing framework to generate unit tests with 100% test coverage.

Spring BootTest AutomationJavaSpring MVCJUnit

Nanyang technological university

Research Internship

May 2021 – Oct 2021 · 5 mos · Singapore

The objective was to explore and implement scalable and robust Federated learning systems with additional privacy
preserving measure to achieve high performance Deep Learning models without having to share data.
Implemented various Federated Averaging algorithms to achieve deep insight on scalabilty, performance and accuracy.
Published and presented a award winning research paper at ICDCS‑IEEE 2022 Italy.
Awarded Best Student Paper Award at 42nd IEEE International Conference on Distributed Computing Systems

Machine LearningPython (Programming Language)Distributed Systems