Jinal Shah

IOS Engineer

Bengaluru, Karnataka, India1 yr 8 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Optimized high-traffic Android app performance significantly.
Developed real-time systems improving rider availability.
Created a scalable UI achieving a 99.95% crash-free rate.

Stackforce AI infers this person is a B2C Android Developer with expertise in high-traffic mobile applications.

Contact

Skills

Core Skills

Android DevelopmentKotlinOptical Character Recognition (ocr)

Other Skills

CoroutinesLifecycle-aware componentsCaching strategiesAndroid APIsServicesGeofencingWorkManagerMQTTJetpack ComposeMVIClean ArchitectureMemory leak fixingAndroidGoogle ML KitFirebase Authentication

About

Android Engineer with experience building and scaling consumer-facing mobile applications using Kotlin, Jetpack Compose, and modern Android architectures. Currently working at Apna Mart, where I focus on performance, reliability, and real-time systems for high-traffic apps with 40K+ daily active users. I approach problem-solving with a customer-centric mindset, aiming to build scalable, reliable, and intuitive Android experiences that directly improve user outcomes and business metrics. Always excited to work on challenging problems at scale 🚀

Experience

1 yr 8 mos

Total Experience

1 yr 5 mos

Average Tenure

3 mos

Current Experience

Slice

SDE - 1

Feb 2026 – Present · 3 mos · Bengaluru, Karnataka, India · On-site

Apna mart

2 roles

Android Developer

Sep 2024 – Feb 2026 · 1 yr 5 mos · Bengaluru, Karnataka, India · On-site

Optimized a high-traffic Android app (40K+ DAU) using Kotlin Coroutines, lifecycle-aware components, and caching strategies, reducing home screen load time by 50% and improving startup time by 800ms.
Built real-time, background-driven systems using native Android APIs including Services, Geofencing, WorkManager, and MQTT, improving rider availability and reducing order reassignment from 33% to 0.03%.
Developed scalable, state-driven UI using Jetpack Compose with MVI and Clean Architecture, while improving app stability by fixing 20+ memory leaks and achieving a 99.95% crash-free rate.

KotlinCoroutinesLifecycle-aware componentsCaching strategiesAndroid APIsServices+8

Android Intern

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

AndroidKotlinAndroid Development

Apps ait

Intern

Oct 2023 – Feb 2024 · 4 mos · Remote · Remote

The project developed an Image-To-OCR Android app using Kotlin and MVVM pattern. It utilized Google ML Kit for image-to-text conversion and language translation, Firebase Authentication for user login, and Cloud Firestore for data management. CameraX and Cropper were used for image capture and cropping, and Razorpay facilitated secure payment transactions. Collaboration via GitHub and Figma ensured efficient code development and version control

KotlinOptical Character Recognition (OCR)