Senior Field Application Engineer - AI

Role Description

We are seeking a Field Application Engineer to join the AI and HPC Center of Excellence. The role broadly involves:

• Working with customers and partners in support of RFP-driven requests.
• Providing hands-on support to customers and partners to enable their AI workloads to run on AMD ‘Instinct’ datacenter GPUs.
• Conducting broader engineering investigations to understand both performance and characteristic performance across popular and customer-specific training and inference workloads.
• Creating a body of technical documentation of AI performance on AMD hardware to support the Field Application team, partners, and customers.

This is a ‘hands-on’ technical role, and we are looking for an individual with an established background in AI who is already familiar with executing and tuning training and inference workloads. In addition to the technical aspect, you will also need to be able to create and deliver presentations and training both remotely and in person to our customers and partners.

The role is based within the United States and will require some travel to customers and conferences both nationally and internationally.

Qualifications

• Track record working within AI.
• 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.
• Skilled in independently prioritizing opportunities to deliver results on time.
• Excellent written and oral communication skills in English.
• Open to travel both domestic and international, approximately 10-20% over a year.

Requirements

• Support winning new AI business by enabling customers to execute their AI workloads on AMD Instinct GPUs, AMD Pensando™ Pollara AI NICs, and EPYC CPUs.
• Build and nurture deep technical relationships with engineers, architects, and leaders at key customer accounts.
• Execute popular and customer-driven AI inference and training workloads, generate results, and create a characteristic understanding of AI performance on AMD hardware.
• Run training and inference performance investigations using common frameworks (Pytorch, Tensorflow, JAX) and using MLperf, Hugging Face, etc.
• Build a body of documentation for internal and external dissemination.
• Proactive engagement across AMD teams providing feedback and leadership from the field on requirements.
• Assist in creating Total Cost of Ownership models to aid pricing with bid desk.
• Technically owning and resolving customer and partner issues.

Preferred Experience

• Demonstrated experience with training and inference workloads on GPUs.
• Executing applications in common frameworks (Pytorch, Tensorflow, Jax).
• Any experience with popular AI repositories (e.g. HuggingFace, MLperf).
• Familiarity with KVM, Kubernetes, Openstack, Openshift.
• Understanding system level hardware design and its impact on performance.
• Understanding how the software stack affects performance.
• Customer-facing experience.
• Some Linux administration; understanding setup for HPC/AI middleware.

Nice to Haves

• Hands-on AI experience within automotive, finance, healthcare, 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.
• Deep Neural Networks and their design for different Machine Learning cases.
• Any experience understanding/inspecting/writing assembly.
• Understanding of memory and cache hierarchy and methods to query performance/latency at each level.
• Datacenter deployment and management experience.
• Government level security clearance.

Academic Credentials

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

Location

• Austin, TX and Remote.

Benefits

• AMD benefits at a glance.