HPC Optimization Engineer-AI/ML Fulltime

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Application Software Optimization Engineer, ML/HPC

THE ROLE:

Would you like to be part of a world class team enabling applications for high performance computing? AMD is searching for talented and highly motivated computational scientists/engineers to join our team of developers preparing applications for supercomputing platforms across industry, academia, and national laboratories.

This position is for a junior to mid-level application optimization engineer in high performance computing, with a focus on optimizing Machine Learning applications.

You will be part of a team porting and tuning a wide variety of scientific applications for AMD CPU and GPU platforms.

THE PERSON:

A computational scientist, physicist, or engineer with experience in multiple scientific computing domains and experience with using Machine Learning techniques in an HPC setting. Must be self-motivated and possess the ability to work well within a team environment.

ACADEMIC CREDENTIALS AND EXPERIENCE:
• Masters or PhD in Computer Science, Computational Physics, Engineering or related subjects, or equivalent experience
• 3-5 years of relevant industry experience

KEY RESPONSIBILITIES:
• Port and optimize a variety of machine learning based applications for AMD CPU and GPU systems
• Provide domain specific knowledge to other groups at AMD
• Engage with AMD product groups to drive resolution of application and customer issues
• Develop and present training materials to internal audiences, at customer venues, and at industry conferences

PREFERRED EXPERIENCE:
• In depth knowledge of current machine learning frameworks and commonly used models
• Experience in scientific computing disciplines such as computational chemistry, fluid dynamics, weather modeling, and oil and gas applications
• Strong performance analysis skills for both CPU and GPU
• Extensive experience with C++ and Python
• Familiarity with distributed model training via NCCL/RCCL, MPI, or similar
• Experience in implementing and optimizing parallel methods on GPU accelerators in distributed memory systems with MPI, CUDA, HIP, OpenMP, etc.
• Broad experience creating, adapting, and running workloads with widely used HPC applications.
• Broad experience building, running and tuning machine learning models.
• In-depth understanding of IO, parallel file systems, and network limitations and capabilities as used in AI models
• Familiarity with installation and setup of various HPC applications and machine learning frameworks
• Experience with build system tools including Make, CMake, autoconf, and autotools
• In-depth knowledge of software development practices including debug, test, revision control, documentation, and bug tracking
• Strong team development skills including demonstrated expertise with git and Jira
• Ability to work well in geographically dispersed teams

LOCATION:

Austin, TX; Santa Clara, CA

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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.