WiFi Machine Learning Engineer for Wireless SoC

Summary
In your role as a WiFi ML Link Adaptation Algorithm Engineer, as part of Apple Connectivity Group, you will be part of a world-class group that pioneers design and development of MAC Layer algorithms for wireless communication systems on Apple products.

We live in a mobile and device driven world where the best wireless performance is required. We rely on this to enable spectacular new features for our customers and make the wireless experience magical.

Apple is designing for these needs as robustly and as creatively as possible and is interested in people who want to help meet this commitment. The success we are targeting will be the result of highly skilled people working in an environment which cultivates creativity, partnership, and solving old problems in new and innovative ways.

If that sounds like the kind of environment that you find intriguing, then let's talk.

Description
We are looking for ML algorithm engineer to innovate and develop advanced rate adaptation and link optimization algorithms for WiFi systems. You will design and develop intelligent algorithms that dynamically optimize wireless transmission parameters to maximize throughput and reliability across diverse channel conditions.

Responsibilities

• Develop algorithms and models to improve rate selection, frame sizes, antenna selection and more with using ML.
• Build/Configure simulation environments modeling fading channels, interference, and multi-user scenarios
• Validate performance of algorithms and models in network and HW simulations across diverse channel conditions
• Convert models and algorithms to embedded firmware implementation
• Create comprehensive test frameworks to evaluate real-world performance
• Conduct over-the-air testing and performance characterization on devices
• Analyze field telemetry data to identify optimization opportunities
• Debug and resolve algorithm-related issues in real-world deployment scenarios
  
  

• BS.c in Electrical Engineering, Computer Engineering, or related discipline
• Experience and proficiency in ML (Neural Networks/CNN)
• Expertise in optimization algorithms with using machine learning and GenAI algorithms, or adaptive control systems
• Proficiency in algorithm development using MATLAB, Python, or similar tools
  
  

• Experience with rate adaptation, link adaptation, or similar adaptive algorithms
• Experience with C/C++
• M.Sc/Ph.D in Electrical Engineering, Computer Engineering, or related discipline
• Knowledge in wireless protocols: WLAN (IEEE 802.11), Bluetooth, Cellular