MTS Software Development Engineer- Machine Learning (158601)

What you do at AMD changes everything

At AMD, we push the boundaries of what is possible. We believe in changing the world for the better by driving innovation in high-performance computing, graphics, and visualization technologies – building blocks for gaming, immersive platforms, and the data center.

Developing great technology takes more than talent: it takes amazing people who understand collaboration, respect, and who will go the “extra mile” to achieve unthinkable results. It takes people who have the passion and desire to disrupt the status quo, push boundaries, deliver innovation, and change the world. If you have this type of passion, we invite you to take a look at the opportunities available to come join our team.

Member of Technical Staff (MTS) for Machine Learning

THE ROLE:

We are currently looking for a Member of Technical Staff (MTS) to drive end-to-end delivery of our DirectML software solution, 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.

THE PERSON:

We are looking for a subject matter expert and strong technical contributor with machine learning and GPU programming experience. The individual will be a member of a team where communication and team skills are highly valued.

KEY RESPONSIBILITIES:

Work within 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 exploits the strengths of the hardware architecture to deliver the best possible machine learning performance.