In your role as a WiFi ML Link Adaptation Algorithm Engineer, as part of our 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 our products.
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.
Requirements: Minimum Qualifications
M.Sc/Ph.D in Electrical Engineering, Computer Engineering, or related discipline.
5+ years of experience and proficiency in ML.
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.
Knowledge in wireless protocols: WLAN (IEEE 802.11), Bluetooth, Cellular.
Preferred Qualifications:
Experience with rate adaptation, link adaptation, or similar adaptive algorithms.
Experience with C/C++.
This position is open to all candidates.