Machine Learning Research Engineer - Embedded Wireless Systems at Apple

Herzliya, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

08 Aug, 26

Salary

0.0

Posted On

10 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Embedded C, Python, MATLAB, C++, Wireless Communications, Real-time Systems, Signal Processing, Federated Learning, Reinforcement Learning, Convex Optimization, Edge Computing, Protocol Design, Neural Networks, Resource Allocation, Distributed ML Systems

Industry

Computers and Electronics Manufacturing

Description

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. You'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 Engineering Real-time Systems: Experience in real-time computing constraints and low-latency system design Machine Learning: Deep understanding of ML algorithms, particularly those suitable for real-time applications (online learning, federated learning, reinforcement learning, neural networks) Wireless Communications: Strong foundation in wireless communication principles, protocols Programming: Proficiency in Embedded C, Python, MATLAB, C++, and ML frameworks Optimization: Experience with convex optimization, resource allocation algorithms, and constraint satisfaction problems Research Experience: Demonstrated track record of independent research through publications, patents, or significant project contributions Knowledge of edge computing and distributed ML systems is advantageous Personal Attributes: Self-Motivated: Ability to work independently, set research priorities, and drive projects from conception to completion Analytical Thinking: Strong problem-solving skills with ability to tackle complex, multi-disciplinary challenges Innovation-Oriented: Creative approach to research with ability to think outside conventional boundaries Communication Skills: Excellent written and verbal communication skills for technical documentation and presentations Collaborative Spirit: Ability to work effectively in cross-functional teams while maintaining independent research focus PREFERRED QUALIFICATIONS Ph.D. in related field

Responsibilities

Research and integrate machine learning algorithms into embedded wireless firmware architectures and protocol designs. Develop proof-of-concept implementations to optimize performance and bridge the gap between theoretical ML and practical wireless systems.