Senior Mobile Developer
About the role
In this role, you'll apply your expertise to help train next generation AI systems. Your work will shape how models learn, reason, and perform through high quality, real world input. As an expert, you will create Reinforcement Learning Environments that test an AI model’s ability to solve complex mobile software engineering problems related to fixing code, creating features, refactoring code, and optimizing performance. You will be tasked with creating a reproducible environment and a golden reference solution for each problem.
What you'll do
- Create realistic, interesting, and extremely challenging mobile coding tasks for frontier AI models using your preferred repositories.
- Design problems that require strong mobile engineering skills, such as tracking down subtle bugs, building non trivial features, handling application state and lifecycle, or improving performance.
- Develop tasks relevant to your expertise: cross platform applications using TypeScript, JavaScript, or Dart; iOS applications using Swift; or Android applications using Kotlin.
- For each task, define the problem, build a reproducible environment, and write deterministic verifiers that accept correct solutions across different valid implementations while rejecting incorrect, incomplete, or hard coded approaches.
- Provide a reference solution showing how the task can be solved.
Requirements
- Preferred: Significant hands on expertise in at least one of the following mobile development tracks:
- Preferred: Cross platform: TypeScript or JavaScript with React Native, or Dart with Flutter.
- Preferred: iOS: Swift with SwiftUI or UIKit.
- Preferred: Android: Kotlin with Jetpack Compose or the Android View system.
- Preferred: Deep understanding of mobile application architecture, state management, asynchronous programming, and application lifecycle.
- Preferred: Proven ability to debug complex mobile applications, resolve bugs, and deliver effective performance improvements.
About micro1
micro1 is a data lab that helps AI labs and large companies train AI models and agents. It finds and checks skilled people from many fields, like law, medicine, finance and coding, to produce the training data that makes AI work better.
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