Machine Learning Research Engineer - Embedded Wireless Systems

Summary

Apple is where wireless innovation transcends the ordinary, creating connections that feel like magic. Every time someone effortlessly switches their AirPods between devices, experiences crystal-clear audio in a crowded room, or enjoys seamless connectivity that just works, they're experiencing the result of our relentless pursuit of wireless perfection. In this role, you'll architect the invisible threads that connect our users to their digital lives. You'll go beyond industry standards, crafting embedded Bluetooth solutions that redefine what's possible. At Apple, wireless is creating experiences so intuitive that the technology disappears, leaving only wonder.nnYou'll work at the intersection of hardware and software, where every microsecond of latency matters and every milliwatt of power is precious!

Description

We are seeking a Machine Learning expert to join our wireless FW software group and explore innovative applications of ML algorithms in embedded wireless systems and protocols. This role focuses on cutting-edge research to integrate machine learning into wireless firmware architectures as well as protocol design, validation, and performance optimization. The position emphasizes experimental research, algorithm development, and proof-of-concept implementations in the wireless FW domain. This role offers the opportunity to develop novel solutions that bridge the gap between theoretical machine learning capabilities and practical wireless system implementations.

Minimum Qualifications

Minimum: Master's degree (MSc) in one of the following fields: Computer Science or Mathematics with specialization in Machine Learning, Signal Processing and Telecommunications EngineeringnReal-time Systems: Experience in real-time computing constraints and low-latency system designnMachine Learning: Deep understanding of ML algorithms, particularly those suitable for real-time applications (online learning, federated learning, reinforcement learning, neural networks)nWireless Communications: Strong foundation in wireless communication principles, protocolsnProgramming: Proficiency in Embedded C, Python, MATLAB, C++, and ML frameworks nOptimization: Experience with convex optimization, resource allocation algorithms, and constraint satisfaction problemsnResearch Experience: Demonstrated track record of independent research through publications, patents, or significant project contributionsnKnowledge of edge computing and distributed ML systems is advantageousnPersonal Attributes: Self-Motivated: Ability to work independently, set research priorities, and drive projects from conception to completionnAnalytical Thinking: Strong problem-solving skills with ability to tackle complex, multi-disciplinary challengesnInnovation-Oriented: Creative approach to research with ability to think outside conventional boundariesnCommunication Skills: Excellent written and verbal communication skills for technical documentation and presentationsnCollaborative Spirit: Ability to work effectively in cross-functional teams while maintaining independent research focus

Preferred Qualifications

Ph.D. in related field