AI/ML iOS Developer (Swift, SwiftUI, Core ML)

SAI CHARAN THUMMALAPUDI

347-***-**** **********@*****.*** GitHub LinkedIn

PROFESSIONAL SUMMARY

Results-driven iOS Developer with nearly 4 years of strong experience building scalable, high-performance mobile applications using Swift, SwiftUI, UIKit, and Apple’s iOS frameworks. Specialized in integrating AI-powered features such as computer vision, NLP, and recommendations into iOS apps using Core ML, Create ML, Vision, and on-device LLMs. Proven ability to collaborate in Agile teams, optimize app performance, and deliver user-centric solutions aligned with current iOS market demand.

CORE COMPETENCIES

AI/ML Integration on iOS, RESTful APIs & Backend Integration, App Performance Optimization & Debugging, Agile / Scrum

& Cross-Functional Collaboration, App Store Deployment & CI/CD Apple Frameworks: Core ML, Vision, AVFoundation, Combine TECHNICAL SKILLS

iOS & Mobile Development

Languages: Swift, Objective-C (basic)

UI: SwiftUI, UIKit, Auto Layout, Storyboards

Architecture: MVVM, MVC, Clean Architecture

State Management: Combine, Async/Await

AI / ML for iOS

On-device ML: Core ML, Create ML

Computer Vision: Vision, Image Classification, Object Detection

NLP: On-device text classification, sentiment analysis

AI Tooling: Hugging Face (model conversion), TensorFlow Lite, PyTorch Core ML

Generative AI: LLM API integration, AI-powered chat features, recommendations Backend & DevOps

RESTful APIs, JSON, URLSession

Firebase (Auth, Firestore, Analytics)

CI/CD: GitHub Actions, TestFlight

Version Control: Git, GitHub

Tools

Xcode, Instruments, VS Code, Postman, Jira

PROFESSIONAL EXPERIENCE

iOS Developer – AI/ML Applications

Walmart, USA Oct 2024 – Present

Designed and developed iOS applications using SwiftUI and UIKit with a focus on performance and accessibility.

Integrated AI-powered features such as image recognition and personalized product recommendations using Core ML and Vision.

Implemented on-device ML inference to reduce latency and improve user experience.

Built and consumed RESTful APIs to connect iOS apps with enterprise backend services.

Collaborated with cross-functional teams to convert TensorFlow/PyTorch models into Core ML format for iOS deployment.

Improved customer engagement metrics by 25% through AI-driven personalization features.

Actively participated in Agile sprint planning, code reviews, and TestFlight deployments. iOS Developer Intern

NVIDIA, USA Mar 2024 – Sep 2024

Developed iOS prototypes showcasing AI/ML use cases such as image classification and NLP-driven insights.

Optimized deep learning models for mobile and edge deployment, ensuring low memory usage and fast inference.

Assisted in converting PyTorch models to Core ML and TensorFlow Lite for iOS integration.

Performed performance profiling using Xcode Instruments to identify and fix memory and CPU bottlenecks.

Supported CI/CD pipelines and participated in sprint demos and technical reviews. iOS Developer / Software Engineer

Nexova, India Jun 2020 – Jun 2022

Built internal iOS proof-of-concept apps to visualize analytics and customer insights for stakeholders.

Integrated backend APIs to fetch analytics and display data in mobile dashboards.

Implemented NLP-based sentiment analysis features and connected them to iOS UI components.

Automated data workflows and supported mobile teams with backend and AI logic.

Worked in Agile teams, aligning mobile solutions with business requirements. EDUCATION

Master of Professional Studies in Data Science University of Maryland, Baltimore County (UMBC) – USA May 2024 Bachelor of Technology in Information Technology Sreenidhi Institute of Science and Technology – India PROJECTS & RESEARCH

Classifiedia App

Technologies: Swift, Xcode, UIKit, Core Data, RESTful APIs, JSON

Developed a user-friendly classified ads app with secure user authentication and listings for cars, furniture, houses, and real estate.

Implemented push notifications and data persistence using Core Data.

Integrated RESTful APIs for data fetching and posting, efficiently handling JSON responses.

Optimized app performance with efficient network calls and data caching strategies. iTunes Artists App

Technologies: Swift, Xcode, UIKit, Core Data, RESTful APIs, JSON

Built an iOS app to browse and search iTunes artists, displaying detailed information, albums, and tracks.

Implemented search functionality and dynamic artist pages for easy discovery.

Integrated the iTunes Search API to fetch artist data and manage JSON responses efficiently.

Enhanced UX with Core Data persistence for offline access and push notifications for updates. LLM-Based Disease Identification & Drug Recommendation System Technologies: Python, NLP, LLMs, Data Analysis, FaissDB

Leveraged NLP techniques and LLMs (LLaMA2) using TensorFlow, PyTorch, and Hugging Face Transformers.

Performed data preprocessing, exploratory data analysis (EDA), and model development following Agile methodology with weekly sprints.

Converted disease and drug data into vectors using instruction and FTE embeddings and stored them in FaissDB.

Implemented fine-tuning techniques including Adapters, Prefix Tuning, and LoRA, achieving 73% accuracy.

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