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Application Software Optimization Engineer, ML/AI
THE TEAM:
AMD's Data Center GPU organization is transforming the industry with our AI based Graphic Processors. Our primary objective is to design exceptional products that drive the evolution of computing experiences, serving as the cornerstone for enterprise Data Centers, (AI) Artificial Intelligence, HPC and Embedded systems. If this resonates with you, come and join our Data Center GPU organization where we are building amazing AI powered products with amazing people.
THE ROLE:
Would you like to be part of a world class team enabling applications for Artificial Intelligence? AMD is searching for talented and highly motivated computational scientists/engineers to join our team of developers preparing applications for AI platforms across the world.
This position is for a senior level application optimization engineer in AI, 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:
An engineer computational scientist, or physicist with experience in multiple scientific computing domains and experience with using Machine Learning techniques in an AI setting. Must be self-motivated and possess the ability to work well within a team environment. Must have experience working with customers in current or previous engineering role.
KEY RESPONSIBILITIES:
- Port and optimize a variety of machine learning based models and 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:
- Broad experience building, running and tuning machine learning models.
- In depth knowledge of current machine learning frameworks and commonly used models for training and inference.
- 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 network technologies.
- Experience in implementing and optimizing parallel methods on GPU accelerators in distributed memory systems with MPI, CUDA, HIP, OpenMP, etc.
- Experience in scientific computing disciplines such as computational chemistry, fluid dynamics, weather modeling, and oil and gas applications.
- 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 AI applications and machine learning frameworks.
- Experience provisioning clusters and validating their performance for use in machine learning applications.
- 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.
ACADEMIC CREDENTIALS:
- Solid years of relevant industry experience.
- Masters or PhD in Computer Science, Computational Physics, Engineering or related subjects, or equivalent experience.
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