Summer 2026 PhD DSP and ML Engineer Intern

Advanced Micro Devices, Inc.•San Jose, CA

44d•Onsite

About The Position

At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. As an AMD intern, you'll be placed at the epicenter of the AI ecosystem, working alongside experts and industry pioneers. You'll do important work, learn new skills, expand your network, and gain real-world experience on projects that impact millions of end-users worldwide. Whether you're an undergrad or a PhD student, your contributions matter-and your experience here will be a launchpad for what comes next. JOB DETAILS: Location: San Jose, CA Onsite/Hybrid: This role requires the student to work full time (40 hours a week), onsite 5 days/week work structure throughout the duration of the intern term. Duration: May 18, 2026 through August 7, 2026 WHAT YOU'LL BE DOING: DFE Technology team develops high performance and low-cost digital front end (DFE) Radio designs for 5G/6G and future base stations with AMD's unique RFSoC and Versal products and influences future device architectures. As a DSP and ML Engineer Intern, you will have the opportunity to work with experienced team members on: Tx/Rx RF modeling in MATLAB for RF Amplifier non-linear responses using advanced ML algorithms Explore various network structures for training and inference engines

Requirements

You are currently enrolled in a US based University into a PhD degree program
Completed Electromagnetic Theory, Matrix Theory, Digital Signal Processing and Digital Communications coursework
Completed coursework in machine learning and various neural networks
Background in non-linear system analysis
Background in RNN, LSTM and other advanced long memory network
Background in Wireless Communications
PhD Candidate - Wired/Wireless Communications background
Strong organizational skills
Strong written & verbal communications
Drive to succeed - we expect our team members to engage with a passion!

Responsibilities

Tx/Rx RF modeling in MATLAB for RF Amplifier non-linear responses using advanced ML algorithms
Explore various network structures for training and inference engines