# Rakesh M. **Senior Android Engineer** — Vancouver, Canada > Senior Android Engineer with 9+ years building high-performance Android apps at Pinterest, DoorDash, and LinkedIn. Experienced in leading teams, system design, and shipping features to hundreds of millions of users. Career Archetype: **Launchpad Artisan** (HS-MX) — One of the first Launchpad Artisans on Saywise ## Links - LinkedIn: https://linkedin.com/in/winnerkm - Portfolio: https://bento.me/winnerkm ## Experience ### AI Android Engineer, League (2025-12 – present) Canada · - Accelerated feature deployment velocity by 10x by architecting an advanced agentic development framework, drastically reducing time-to-market for core product capabilities. - Leveraged cutting-edge foundational models within an autonomous workflow to automate complex engineering asks and rapidly ship high-value features. - Designed and engineered robust agent harnessing systems, implementing strict guardrails and evaluation layers to guarantee deterministic and safe AI behaviors. - Mitigated operational risks and ensured product reliability by building continuous validation pipelines to audit agent-generated output against enterprise security standards. ### Senior Software Engineer, Pinterest (2024-10 – 2025-12) Remote, Canada · Led development of ad solutions for 500M+ users. Designed and implemented a state-based architecture to improve code quality and app responsiveness. Worked cross-functionally with product, design, and data science teams to optimize features. Focused on performance tuning and scalability. ### Senior Android Engineer & Team Leader, DoorDash (2021-12 – 2024-10) Toronto, ON · Managed a team of 5 Android Engineers building ads, promotions, and DashMart features for the Consumer app. Enhanced backend systems resulting in 5% increase in ad traffic and DashPass conversion rates. Led development of in-store scan feature for DashMart. Delivered $250k-$300k in annual net profits through effective leadership. ### Senior Software Engineer, LinkedIn (2020-04 – 2021-10) Bengaluru, Karnataka, India · Led a team of 4 Android Engineers for LinkedIn Groups and Events. Transitioned from REST API to GraphQL and implemented dependency injection, reducing page load times by 20%. Rewrote legacy LinkedIn group code with modern Android tools, achieving 100% crash-free sessions. Optimized feature addition time by 50%. ### Senior Software Engineer, Paytm Money (2019-04 – 2020-02) Bengaluru, Karnataka, India · - Played a pivotal role in the development of Paytm Money, starting from its initial stages and scaling the app to over 10 M+ downloads. - Contributed to setting up the Android app architecture using technologies such as MVVM with Clean architecture, RxJava, Data Binding, Dagger2, Kotlin, Modularized Architecture, and Room DB. - Actively participated in code reviews, brainstorming sessions, and team meetings. ### Software Engineer, Paytm Money (2017-12 – 2019-03) Bengaluru Area, India ### Android Engineer, Kuliza (2016-01 – 2017-11) Bengaluru, Karnataka, India ### Senior Android Engineer, PaytmMoney (2016-01 – 2020-02) Bengaluru, India · Built Paytm Money from initial stages to 10M+ downloads. Set up Android app architecture using MVVM with Clean architecture, RxJava, Data Binding, Dagger2, and Room DB. Actively participated in code reviews, brainstorming sessions, and team meetings. ## Education ### Bachelor of Technology (B.Tech.) in Information Technology, Indian Institute Of Information Technology Allahabad Activities and societies: Computer Science ## Projects ### Spam Email Classification The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Machine learning techniques now days used to automatically filter the spam e-mail in a very successful rate. In this project we build some of the most popular machine learning methods (Multinomial Bayesian classification, K-NN and SVMs) and compare their performance with respect to each other. Tools Used: LIBSVM Languages Used: Java, C++ ### Parallel K-means Clustering This project is aimed at adapting Parallel K-means algorithm based on map reduce framework using Hadoop to make the clustering method applicable to large scale data. We compared parallel k-means with serial k means. We use speedup, scaleup and sizeup to evaluate the performances of our proposed algorithm. The results show that the proposed algorithm can process large datasets on commodity hardware effectively. Tools Used: Apache Hadoop version 1.2.1. ### Online Shopping System The Main aim of this project is to design Online shopping System which is used to provide a online interface to E- users (online users ) to buy and sell goods by sitting at home through internet. we designed back-end using java and used oracle 10g for data storage !! Languages Used: Java. Tools Used: Netbeans, Oracle10g. ## Skills Software Infrastructure, Android Framework, Object Oriented Design, Model-View-Controller (MVC), Kotlin Coroutines, Backend, Microservices, Apache Kafka, Kubernetes, Amazon Web Services (AWS), Redis, Continuous Integration and Continuous Delivery (CI/CD), Project Estimation, Unit Testing, Google Analytics, Git, Team Leadership, Spring Boot, Java, Android, Model-view-viewmodel (MVVM), Programming, Algorithms, Data Structures, Engineering, Software Development, Android Development, Image Editing, Architecture, Mobile Devices, Basic HTML, Kotlin, XML, Firebase, GitHub, Python (Programming Language), Competitive Programming, mvp, coding, Software Engineering Practices, Mobile Photography, Mobile Application Development, Android Design, C++, MVI architecture, Jetpack Compose, Dependency Injection, Dagger, Hilt, RESTful APIs, GraphQL, RxJava, Data Binding, Room DB, Coroutine, Agile, Scrum, Code review, Monitoring and alerting systems, Automated testing, Espresso, JUnit, Functional programming ## Credentials - **Editing Images Using Snapseed** — LinkedIn (issued 2020-05) - **Kotlin for Android: Best Practices** — LinkedIn (issued 2020-05) - **Photography Foundations: Mobile Photography** — LinkedIn (issued 2020-05) - **Flagship Android 101: Introduction to Lever** — LinkedIn (issued 2020-04) ## AI Fluency - **Claude** — Daily (https://claude.ai) --- Source: https://saywise.com/member8324 (last modified 2026-10-06T06:28:23.919Z)