Senior Machine Learning Engineer (Santa Clara or Austin) - 134693

Location: Santa Clara, California, US

Company: Advanced Micro Devices

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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.
 

Senior Machine Learning Engineer (Santa Clara or Remote Opportunities)

 

Our team ensures customers and application development teams understand and realize the full potential of AMD's Data Center Instinct GPU products. Researcher mindset, engineering execution. We're looking for a candidate with expertise in Python, PyTorch, and a proven track record of profiling, optimizing, and deploying machine learning applications for production environments. The ideal candidate will have a strong background in methods for reproducible research, data visualization, and the technical communication skills necessary to compile planning and reporting deliverables with data-driven statistical analysis.

 

KEY RESPONSIBILITIES

  • Optimize the performance of Machine Learning workflows for AMD GPUs and platforms
  • Define performance suite and best practices for measuring GPU accelerated Machine Learning workloads
  • Work with a talented and diverse team to benchmark and analyze ML workloads at data center scale
  • Own Datacenter GPU performance analysis for use in engineering, product development, and product marketing
  • Perform deep performance analysis and report findings for the entire platform including GPU, CPU, interconnects, network, software stack, etc.
  • Identify performance bottlenecks that impact datacenter GPU accelerated workloads, and collaborate with software teams to improve performance
  • Participate in community-developed benchmarks like MLCommons MLPerf
  • Coach and mentor less experienced team members and influence others as a technical leader
  • Evolve team talent pipeline for our expanding team

 

PREFERRED EXPERIENCE

  • In-depth experience in Machine Learning (ML), Deep Learning (DL), or Artificial Intelligence (AI), training and inference production use cases
  • Understanding of Deep Learning algorithms, e.g. CNN, LSTM, RNN
  • Experience with Deep Learning frameworks, such as PyTorch
  • Excellent programming skills in languages such as Python
  • Experience with performance analysis tools and techniques
  • Solid understanding of Computer Architecture and Operating systems
  • Ability to scope and deliver projects on time
  • Collaborator with strong written and verbal communication skills
  • Experience with GPU accelerated compute applications with either AMD or Nvidia / CUDA products a plus

 

ACADEMIC CREDENTIALS
 

  • Minimum B.S. degree in Computer Science or Engineering or similar field

 

Location:  The team is based in Santa Clara, CA, but we are open to hiring the following AMD sites (Austin, TX, Bellevue, WA, Orlando, FL, San Diego, CA, and Boxborough, MA).

 

#LI-RL1


Requisition Number: 134693 
Country: United States State: California City: Santa Clara 
Job Function: Design
  

 

AMD does not accept unsolicited resumes from headhunters, recruitment agencies or fee based recruitment services. AMD and its subsidiaries are equal opportunity employers. We consider candidates regardless of age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status. Please click here for more information.

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