Application Software Optimization Engineer, High Performance Computing and AI

October 21, 2024

Industry: Private

Employment Type:- Full Time

Work Hours:- 8 Hours

Locations:- USA

Full Job Description:-

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.

Responsibilities:

Application Software Optimization Engineer, High Performance Computing and 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 joining 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 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 variable experience level optimization engineer in high performance computing. This ranges from junior / entry level to experienced GPU programmers.

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

THE PERSON:

A computational scientist, physicist, or engineer with experience in at least one scientific computing domain and strong GPU programming skills. A track record of collaborating with others on applications and libraries widely used by the scientific computing community is a plus. Must be self-motivated and possess the ability to work well within a team environment.

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ACADEMIC CREDENTIALS AND EXPERIENCE:

Masters or PhD in Computer Science, Computational Physics, Engineering or related subjects
Advanced candidates bring an additional 3-5 years of relevant industry experience
GPU programming experience of at least two years in an academic or industrial setting is highly desired
Working knowledge of a major AI framework (PyTorch / TensorFlow) or exposure to a converged HPC/AI code is a plus

KEY RESPONSIBILITIES:

Port and optimize a variety of scientific applications for AMD 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 one scientific computing discipline such as finite element analysis, computational chemistry, fluid dynamics, weather modeling, and oil and gas applications
Extensive experience with modern Fortran or C/C++
Strong performance analysis skills ideally for both CPU and GPU
Experience in implementing and optimizing parallel methods on GPU accelerators in distributed memory systems with MPI, CUDA, HIP, OpenMP, etc.
Experience with a converged HPC/AI application is a plus
Broad experience creating, adapting, and running workloads with widely used HPC applications is a plus
Familiarity with installation and setup of various HPC applications is a plus
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
Ability to work well in geographically dispersed teams