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About the Role

We are seeking an AI Application Engineer to join the HPC Centre of Excellence (HPC CoE). This hands-on technical role involves supporting customers and partners with AI workloads on AMD datacenter GPUs, conducting engineering investigations, and creating technical documentation. The role offers an opportunity for growth and significant business impact with executive visibility.

Responsibilities

Support winning new AI business by enabling customers to execute AI workloads on AMD Instinct GPUs and EYC CPUs.
Support partners in RFP responses by testing requested workloads.
Liaise and advise customers and partners through Proof of Concepts (POCs), presentations, and training.
Execute popular and customer-driven AI inference and training workloads, generate results, and create a characteristic understanding of AI performance on AMD hardware.
Understand how system and software choices affect performance and compare performance to competition.
Run training and inference performance investigations using common frameworks (Pytorch, Tensorflow, JAX) and tools like MLperf, Hugging Face.
Build a body of documentation for internal and external dissemination, including AMD-internal guides, whitepapers, tuning guides, and training collateral.
Proactively engage across AMD teams (GPU Business Unit, Engineering, Architecture, Platform, Software, Product Development) to provide feedback and leadership from the field.
Gather missing functionality requirements and work with Engineering to resolve and test.
Assist in creating Total Cost of Ownership models to aid pricing with the bid desk.
Technically own and resolve customer and partner issues, submitting JIRA tickets and driving resolution.

Requirements

Track record working within AI, currently undertaking AI inference or training as a key part of your function.
Demonstrable hands-on expertise working with popular AI frameworks.
Strong positive can-do attitude willing to do what is necessary and lead others in the wider FAE team by example.
Available to help colleagues.
Skilled in independently prioritizing opportunities to deliver results on time.
Excellent verbal and written communication skills.
Open to travel both domestic and international, approximately 10-20% over a year.
Good English.
Demonstrated experience with training and inference workloads on GPUs.
Executing applications in common frameworks (Pytorch, Tensorflow, Jax).
Familiarity with popular AI repositories (e.g. HuggingFace, MLperf) and understanding derived performance/functionality differences between them.
MLops familiarity with KVM, Kubernetes, Openstack, Openshift.
Understanding system level hardware design and its impact on performance.
Understand how the software stack affects performance: frameworks, precision, compilers, libraries, and other accompanying middleware applications.
Customer-facing experience.
Able to write technical documents and communicate at an appropriate level depending on the audience.
Some Linux administration; understanding setup for HPC/AI middleware.
Hands-on AI experience within automotive, finance, enterprise, defense verticals.
Programming experience with any of HIP, CUDA, Python, C/C++, Fortran, OpenACC, OpenMP, pSTL.
Understanding impact of inter-node network choices on performance at scale.
Creating performance projections for applications.
Deep Neural Networks and their design for different Machine Learning cases.
Experience understanding/inspecting/writing assembly.
Understanding of memory and cache hierarchy and methods to query performance/latency at each level.
Inspecting and dataflow down to the register-level.
Government level security clearance.

Skills

AI
AI inference
AI training
AI frameworks
AI performance
Pytorch
Tensorflow
JAX
MLperf
Hugging Face
MLops
KVM
Kubernetes
Openstack
Openshift
Linux administration
HIP
CUDA
Python
C/C++
Fortran
OpenACC
OpenMP
pSTL
Deep Neural Networks

Location

Tokyo, Japan

Work Type

Hybrid
Domestic travel
International travel

Experience Level

Established background in AI
Familiar in executing and tuning training and inference workloads
Demonstrated experience with training and inference workloads on GPUs
Customer-facing experience

Education Level

Bachelors' Degree in a technical field (Computer Science, Electrical Engineering, Physics, Mathematics) preferred

Benefits

AMD benefits at a glance

About the Company

At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward.

Equal Opportunity

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.