Entry Level Staff System Software Engineer, Android OS

Entry Level Staff System Software Engineer, Android OS - Remote Job, US/Canada, 1+ Year Experience About us: Patterned Learning is an AI-powered platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.

After applying for a position, please follow our page for further updates. Requirements What You’ll Do: Design and develop high-performance firmware and software for cutting-edge IoT platforms. Debug, optimize, and validate firmware on complex multi-core architectures. Develop automated and unit-level functional testing to validate designs. Present and provide feedback on architectural discussions for next-generation business logic.

Engage with a cross-disciplinary team to design, develop, and test features up the stack. Validate and maintain features using cloud-based analysis at scale What We’re Looking For: 1+ years of experience in software development Bachelor’s degree in Computer Science, Computer Software Engineering, Electrical Engineering, or equivalent experience Experience with Kotlin, Java & C++ Deep experience with AOSP (Android Open Source Project), Android OS, and Linux Experience with embedded programming on Linux and/or RTOS Why Patterned Learning AI?

By leveraging AI, Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This AI-powered assistance can help reduce coding errors, improve productivity, and accelerate the development process. The use of AI in pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks.

These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.