Senior Android Engineer - AI Platform at Yonder Media Mobile

, , Poland -

Full Time

Start Date

Immediate

Expiry Date

01 Aug, 26

Salary

0.0

Posted On

03 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Android SDK, Kotlin, Java, C++, JNI, NDK, Android Lifecycle, Foreground Services, Doze Mode, Play Store Policies, Battery Optimization, Thermal Management, NPU, TensorFlow Lite, ExecuTorch, ONNX Runtime

Industry

Telecommunications

Description

Senior Android Engineer - AI Platform About the Role Yo is building an AI inference platform that runs directly on smartphones - turning the phone in your pocket into part of a global AI network. You will own the Android side: building the runtime that uses Qualcomm, MediaTek, Samsung, and Google NPUs to run real AI models on real devices while the phone sits on the charger. This is a foundational hire. You set the Android technical direction from day one and ship code that runs on millions of devices, across the full spread of OEMs and chipsets. ## Key Responsibilities - Own the Android SDK end-to-end - architecture, public API, distribution, versioning - Build and maintain the Android runtime that runs AI inference across the major NPU vendors - Handle the long tail of Android hardware fragmentation - flagship to mid-range - Make it fast, battery-friendly, and thermally well-behaved at sustained load - Manage the lifecycle correctly within Android foreground-service and battery-optimisation rules - Work with the iOS engineer to keep the two platforms feature-aligned - Ship to production and iterate against real-world telemetry ## Required Qualifications - 6+ years Android engineering experience - Strong Kotlin and Java; comfortable with C++ and JNI / NDK - Deep understanding of Android lifecycle, foreground services, Doze mode, and Play Store policies - Experience with system-level constraints: battery, thermal, memory pressure - Has shipped production code across a wide range of OEMs and chipsets ## Nice to Have - On-device ML experience (TensorFlow Lite, ExecuTorch, ONNX Runtime, llama.cpp on Android) - NPU SDK experience: Qualcomm QNN, MediaTek NeuroPilot, Samsung ENN, Google AICore - Quantised model formats (INT4 / INT8, GGUF) - Has shipped a public SDK or library used by other developers - Cryptography fundamentals - end-to-end encryption, attestation, hardware-backed keystore - Open-source contributions to ML inference projects ## What Success Looks Like (First 6 Months) - Working Android SDK shipped to a pilot user base - Production telemetry showing measured battery and thermal impact - Stable runtime across flagship, mid-range, and entry-level devices - Clean foundation for the team to build on ## Location & Logistics - Remote / flexible (team in EU and US time zones) - Competitive senior compensation, equity participation - Reports to the CTO

Responsibilities

You will own the end-to-end architecture and development of the Android SDK for an AI inference platform. This involves building a battery-efficient runtime that leverages NPU hardware across diverse Android devices.