Android Application Engineer
Lilt- Lega Italiana per la Lotta contro i Tumori
San Francisco, CA, US
Onsite
2026-06-21
Typical pay for this role in San Francisco
$119K - $214K
Low
$119K
Median
$166K
High
$214K
Official salary benchmark · BLS OEWS 2025
Job description
**About LILT**
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**AI is changing how the world communicates — and LILT is leading that transformation.**
We're on a mission to **make the world's information accessible to everyone**, regardless of the language they speak. We use cutting\-edge **AI, machine translation, and human\-in\-the\-loop** expertise to translate content faster, more accurately, and more cost\-effectively without compromising on brand, voice, or quality.
At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues—**Work together, win together; Find a way or make one; Quicker than they expect; Quality is Job 1**—guide everything we do. We are trusted by Intel Corporation, Canva, the United States Department of Defense, the United States Air Force, ASICS, and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category\-defining company in a $50B\+ global translation market being redefined by AI.
LILT is looking for an Android Application Engineer to join the team building LILT Converse, our on\-device instant translation application. Converse enables secure, real\-time speech translation without an internet connection — making it the go\-to solution for government, defense, and enterprise teams operating in communication\-sensitive or connectivity\-constrained environments. You will work at the intersection of cutting\-edge on\-device AI and polished mobile UX, building software that runs large multilingual speech models directly on Android hardware leveraging Qualcomm Snapdragon AI acceleration. This is a high\-impact role on a product that is moving quickly.
As the Android engineer on Converse, you will own the Android application end\-to\-end — from architecture and on\-device ML integration through performance tuning, release, and reliability in the field — working closely with ML, product, and design on a small senior team. You will archite