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Desert Ant Labs in Amsterdam is seeking an Android performance engineer to speed up machine learning models on mobile chips across devices, including budget phones and flagships. You will profile and optimize inference in Android runtimes and write native code with JNI to improve library performance.
You will test on a range of Android devices in our labs and Firebase Test Lab, maintain an Android library used by external developers, and collaborate to ship fast, reliable code.
Build our Kotlin SDK, and find the fastest way to run each model on each Android chip.
Location Amsterdam, Remote
Time zone UTC-5 to UTC+1
Type Full time
Android phones use hundreds of different chips, NPUs, and drivers. You speed up each model, across audio, vision, and text, until the model meets its latency target on a budget phone as well as on a flagship. Deep Android performance experience matters more here than machine learning experience.
Start what needs starting without waiting to be asked, and finish what you start. Take on work outside your role when a project needs you.
We ship quickly, so we cut scope until only the part users notice is left. Anyone can comment on your work or redo your draft, and we say early when work isn't ready. We read that feedback as help.
We judge the work by what shipped and what changed because of it. Nobody counts hours.