Raghav is a senior mobile engineer who has progressed from aerospace systems software to consumer Android, demonstrating depth in performance optimization (25% crash reduction), modern Android architecture, and safety-critical feature delivery. His career reflects a transition to high-impact consumer products with technical breadth spanning Kotlin, AOSP, and on-device ML.
Route to Android Architect, Android Tech Lead, Mobile Engineer teams building high-throughput services in the candidate's core stack.
Kotlin & Jetpack Compose mastery with production-scale architecture. Performance optimization & memory leak debugging (LeakCanary, profiling). On-device ML integration and safety-critical feature delivery. AOSP framework development and system-level platform integrations.
ML/AI Engineer, Android Engineer, Mobile Engineer, Performance Engineer.
Remote-first. Hybrid considered for high-alignment local roles. Based in Phoenix, US.
Targeting $100K+. Currently: Android Engineer.
Recruiter screen → hiring-manager review → technical conversation around Device Metrics Feature, Maestro Test Automation, Memory Optimization Initiative.
Raghav's work in ML/AI Engineer, Android Engineer, Mobile Engineer translates directly into adjacent domains with similar architecture, scale, and reliability needs.
This reusable proof index maps common senior/staff engineering requirements to candidate proof. Role-specific addenda extend — not replace — this base matrix.
Requirement: Deliver on device metrics feature at production scale.
Proof: Real-time monitoring across thousands of paired devices with Kotlin/MVVM/LiveData
Requirement: Deliver on maestro test automation at production scale.
Proof: Introduced automated regression coverage for critical onboarding and monitoring workflows
Requirement: Deliver on memory optimization initiative at production scale.
Proof: ~25% reduction in memory-related crashes through LeakCanary debugging and rendering optimization
Requirement: Deliver on ml nudity detection pipeline at production scale.
Proof: On-device ML safety feature protecting underage users from unsafe visual content
Requirement: Ship work that requires kotlin & jetpack compose mastery with production-scale architecture.
Proof: Demonstrated at prior roles.
Requirement: Ship work that requires performance optimization & memory leak debugging (leakcanary, profiling).
Proof: Demonstrated at prior roles.
Real-time monitoring across thousands of paired devices with Kotlin/MVVM/LiveData
Introduced automated regression coverage for critical onboarding and monitoring workflows
~25% reduction in memory-related crashes through LeakCanary debugging and rendering optimization
On-device ML safety feature protecting underage users from unsafe visual content
Mid — role fit: adjacent.
Senior — role fit: primary.
Senior — role fit: primary.
Senior — role fit: secondary.
github.com/RaghavGupta13 — public repositories, contribution activity, and open source project surfaces.
https://pypes.dev/raghav-gupta
Hosted candidate portfolio with positioning, proof points, and conversion kit surface for recruiter routing.
www.linkedin.com/in/raghav-gupta-1381a9153/?isSelfProfile=false
Professional profile and recruiter connection path.
This kit is designed to survive internal forwarding. The fastest next step is a recruiter screen, hiring-manager review, referral handoff, or direct call.
Primary fit: Android Architect, Android Tech Lead, Mobile Engineer.
Fastest way to reach Raghav — grab a slot on their calendar.
Persistent candidate surface for routing, resume, and proof surfaces.
Professional profile and recruiter connection path.
Public engineering surface, repositories, and OSS project path.
Additional candidate-owned portfolio and technical writing surface.
Raghav Gupta is a Phoenix, US-based Android Architect. Raghav is a senior mobile engineer who has progressed from aerospace systems software to consumer Android, demonstrating depth in performance optimization (25% crash reduction), modern Android architecture, and safety-critical feature delivery. His career reflects a transition to high-impact consumer products with technical breadth spanning Kotlin, AOSP, and on-device ML. Best fit: Android Architect, Android Tech Lead, Mobile Engineer.