Mobile Engineer - Full time On-site (Internships available too)
About the role
About Besimple AI
Besimple AI is building the audio data and evaluation infrastructure for real-world voice AI deployment. We help AI teams collect, evaluate, and improve voice models across languages, accents, environments, and complex human interactions.
The founders are ex-Meta product and engineering leaders from MIT and Brown. We are a small, high-ownership team working directly with frontier AI labs and fast-moving AI companies to push the state of the art in audio models, voice agents, and human-in-the-loop evaluation.
About the role
We are looking for a full-time Mobile Engineer lead to own the mobile experience for our contributor data collection platforms.
This is a high-ownership role at the intersection of mobile engineering, audio recording, user experience, product, and AI data quality. You will own the mobile experiences that allow people around the world to record, review, submit, and improve audio data used to train and evaluate frontier voice AI systems.
This is not a generic app development role. You will work on real production workflows where mobile UX directly affects audio quality, contributor throughput, customer delivery, and model performance.
What you’ll do
- Build and maintain a mobile platform that will be used by tens of thousands of users for onboarding, audio recording, and live conversations.
- Own mobile features from product requirements through implementation, release, monitoring, and iteration.
- Work closely with founders, product, design, backend, and operations to turn messy real-world workflows into simple mobile experiences.
- Improve audio capture quality, upload reliability, offline behavior, latency, permissions, device compatibility, and error recovery.
- Build contributor-facing flows for recording tasks, auditions, metadata collection, QA feedback, payments, and project instructions.
- Instrument mobile workflows so we can understand conversion, task completion, audio quality, rework, and drop-off.
