About this role

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

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
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

Senior Android Engineer – AI Platform

Key skills