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.
 

Data Center GPU Performance Engineer - Deep Learning

THE ROLE

Our team elevates the impact of AMD's data center GPU products by leveraging performance features uniquely designed for Deep Learning applications. We are seeking an engineer to join our team that will thrive in a fast-paced work environment, using strong communication, problem-solving and prioritization skills. Individuals that are well organized, show great attention to detail, and employ critical thinking are well-suited for our team.

KEY RESPONSIBILITIES:

• Optimize the performance of Deep Learning models for AMD GPUs and platforms
• Define performance suite and best practices for measuring GPU accelerated Machine Learning / Deep Learning workloads
• Own Datacenter GPU performance and market competitiveness for use in product development, product marketing and engineering
• Perform statistical analysis and report outcomes, not only GPU performance but other system variables that impact performance -- CPU, RAM, OS, drivers, etc.
• Identify performance bottlenecks that impact datacenter GPU accelerated workloads, and collaborate with other software teams to find solutions
• Build and support submissions for community benchmarks like MLPerf

PREFERRED EXPERIENCE:

• Expertise in Machine Learning (ML), Deep Learning (DL), or Artificial Intelligence (AI), particularly for training
• Understanding of Deep Learning algorithms, e.g. CNN, LSTM, RNN
• Experience with Deep Learning frameworks, such as PyTorch, TensorFlow, ONNX Runtime
• Excellent programming skills in languages such as Python or C/C++
• Knowledge of Computer Architecture and/or Operating systems
• Strong interpersonal skills, written and oral

WAYS TO STAND OUT:

• Experience with GPU acceleration with either AMD or Nvidia / CUDA products
• Background with performance analysis and profiling of workloads

ACADEMIC CREDENTIALS:

• B.S./M.S. degree in Computer Science or Engineering or similar field or equivalent experience