Job Description

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WHAT YOU DO AT AMD CHANGES EVERYTHING

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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.

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THE ROLE:

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A senior technical contributor that drives end-to-end delivery of software solutions, directly contributing to, and coordinating implementation and optimization across multiple teams for inference and training of machine learning models. The position will involve interfacing with software and hardware engineering teams and AMD partners to plan, develop and optimize use cases. This is an exciting opportunity to work on the cutting edge of GPU Computing for Machine Learning.

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THE PERSON:

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You are a subject matter expert and strong technical contributor with machine learning and GPU programming experience. You excel as part of a team where communication and team skills are highly valued.

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KEY RESPONSIBILITIES:

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• Work within and coordinate with a small team to analyze, implement, and optimize DirectML-TensorFlow and PyTorch for machine learning models
• Collaborate with ISV, library, compiler, driver, and hardware engineers to influence strategic decisions to achieve the highest performance for DirectML
• Innovate new algorithmic improvements that exploit the strengths of the hardware architecture to deliver the best possible machine learning performance

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PREFERRED EXPERIENCE:

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• Relevant experience in Machine Learning and/or GPU programming
• Experience in deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe, ONNX, etc) and familiarity with CNN/LSTM model architectures
• Knowledge of CPU and GPU architecture, and experience in GPGPU programming technologies
• Experience advocating for technical solutions in a collaborative team environment
• Excellent communication and collaboration skills

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ACADEMIC CREDENTIALS:

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Bachelor’s or Master’s degree in related discipline preferred

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