Job Overview:
The Pre-Silicon Engineer role at Apple’s Machine Learning and AI department involves implementing new functional features in the compiler stack using the Apple Neural Engine simulation environment, focusing on performance and power optimization. You will collaborate with hardware teams to review specifications, understand design goals, and contribute to architectural changes for future ANEs. Additionally, you will develop features for future products, from concept through hardware bringup and validation, while working closely with driver/firmware teams to integrate HW acceleration into the software stack. This role requires a strong background in SoC/GPU acceleration for AI, hardware reference models, and deep learning workloads, along with excellent programming skills in C/C++ and problem-solving abilities.
>> View full job details on Apple’s official website.
Resume and Interview Tips:
To tailor your resume for the Pre-Silicon Engineer position at Apple, emphasize your hands-on experience with SoC or GPU acceleration for AI, as this is a core requirement. Highlight specific projects where you worked with hardware reference models, performance and power models, or SW/HW parallelism. Detail your contributions to embedded systems or real-time OS development, as these are key qualifications. Showcase your proficiency in C/C++ programming and any relevant work with deep learning workloads. Quantify your achievements where possible, such as performance improvements or successful hardware integrations. Additionally, include any collaboration with cross-functional teams, as teamwork and communication are highly valued. A master’s degree in Computer Science or a related field is essential, so ensure your education is prominently featured.
During the interview for the Pre-Silicon Engineer role, expect deep technical questions about your experience with SoC/GPU acceleration, hardware models, and performance optimization. Be prepared to discuss specific projects where you tackled performance gaps or contributed to architectural changes. Practice explaining complex technical concepts clearly, as excellent communication is a key requirement. You may also face problem-solving scenarios or debugging exercises, so brush up on your C/C++ skills and debugging techniques. Demonstrating your ability to collaborate with hardware and software teams will be crucial, so highlight instances where you worked across disciplines. Finally, research Apple’s ANE technology and be ready to discuss how your skills align with their goals for future hardware and software integration.