Lakshya Garg

Software Engineer

Ghaziabad, Uttar Pradesh, India0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Strong background in computer science and software development.
Experience in developing AI-driven applications.
Proficient in multiple programming languages and frameworks.

Stackforce AI infers this person is a skilled AI and software development intern with a focus on backend and machine learning technologies.

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Skills

Core Skills

Deep LearningSoftware Development

Other Skills

AirflowAlgorithmsAmazon DynamodbBack-End Web DevelopmentC++Cascading Style Sheets (CSS)Cloud ComputingCommunicationComputer ScienceComputer VisionData StructuresDockerEngineeringEnglishExpress.js

About

As a highly motivated and results-driven individual, I have a strong background in computer science, software development and AI. My education and work experience have equipped me with a wide range of technical skills, including proficiency in various programming languages and frameworks. In addition to my technical expertise, I have also held positions of responsibility, demonstrating my leadership skills and ability to work effectively in a team.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Juleo

Backend Engineer Intern

Dec 2024 – May 2025 · 5 mos · Gurugram, Haryana, India · On-site

Match Maker and AI

Google

Software Engineer Intern

May 2024 – Aug 2024 · 3 mos · Bengaluru, Karnataka, India · On-site

Worked in the Google Cloud Memorystore team. Worked on developing secondary indexing for an in memory VectorDB.

Samsung india

PRISM Developer Intern

Jul 2023 – Mar 2024 · 8 mos · Remote

Worked on developing a light weight Pet Action Recognition Engine using Deep Learning techniques

Graebert - ares cad software

SWE Intern

Jun 2023 – Jul 2023 · 1 mo · Noida, Uttar Pradesh, India · On-site

Worked in the desktop team developing ARES Commander, a CAD software for 2D and 3D design.
Primarily worked on mention user feature in cloud drawings, allowing users to tag and notify other collaborators.
Final implementation was made platform independent by adding custom wrapper for each platform i.e. Mobile, Desktop & Cloud.