Deep Learning Library GPU Software Development Architect - Performance AI Libraries

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The ROLE:

AMD is looking for an individual to join a hardworking team developing Deep Learning and High-Performance Computing GPU kernels on the AMD Radeon Open Compute (ROCm) platform (https://github.com/ROCmSoftwarePlatform) and MIOpen (https://github.com/ROCmSoftwarePlatform/MIOpen), AMD's Deep Learning primitives library which provides highly-optimized implementations of a variety of operators.

The PERSON:

The successful person will be an experienced programmer with experience in performance optimization on convolution and other critical AI performance operators on GPU and other massive parallel processing environment.

KEY RESPONSIBILITIES:

• The ideal candidate will be responsible for architecting and supporting for AMD's Machine Learning and Deep Learning Library: MIOpen (https://github.com/ROCmSoftwarePlatform/MIOpen)
• The candidate should have experience with deep learning training and inference workloads optimization on massive parallel hardware and software platforms.
• They will be responsible guiding performance optimizing algorithms for new GPU hardware.
• Perform code reviews, build unit tests, author detailed documentation related to their work, and work with on-site and offshore teams to deliver the software solutions on schedule.
• They will play a key role in all phases of the software development including system requirements analysis, coordinating feature design and development across functional and organizational boundaries.
  
• They will be driving new hardware and software co-design to optimize state-of-the-art deep learning workloads, and leading the collaboration from hardware, compiler, to a variaty of deep learning frameworks

PREFERED EXPERIENCE:

• Strong programming skills in software architecture in C/C++, and background in machine learning and deep learning, particularly in training.
• Experience with analyzing and tuning performance optimization for GPU computing is preferred.
• Experience or knowledge about deep learning primitives, fusion, and inference optimization is preferred.
• Strong knowledge of software development lifecycle, SW practices including debugging, test, revision control, documentation, and bug tracking.
• Good teamwork and interpersonal skills required.
• Ability to work independently and within complementary teams.
• Demonstrate flexibility, strong motivation, and a proven track record of meeting results-oriented deadlines.
• Knowledge with deep neural network machine learning technologies and modern machine learning programming frameworks.
• Experience working with and developing virtualization containers and package managers for code deployment.
  
  

ACADEMIC CREDENTIALS:

PhD or Master's in Computer Science, Computer Engineering, or related subjects, or strong and equivalent experience

LOCATION: Austin, TX

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At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD's Employee Stock Purchase Plan. You'll also be eligible for competitive benefits described in more detail here.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to 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, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.