Responsibilities
THE ROLE:
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 broader engineering investigations to understand both performance and characteristic performance across popular and customer-specific training and inference workloads. Understand competitive positioning 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 in 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.
AMD continues to ramp its in-house AI expertise, and as such this role provides an opportunity for the candidate to grow within the role while creating a significant impact on the wider business, with significant visibility to executive level within AMD.
The role is based within the United States and will require some travel to customers and conferences both nationally and internationally.
THE PERSON:
Does this sound familiar? We'd love to talk!
Track record working within AI. You are currently in a role 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 written and oral communication skills in English, with the ability to collaborate effectively with both management and engineering teams.
Open to travel both domestic and international, approximately 10-20% over a year.
KEY RESPONSIBILITIES:
- Support winning new AI business. Enabling customers to execute their AI workloads on AMD Instinct GPUs, AMD Pensando™ Pollara AI NICs, and EPYC CPUs. Supporting partners in RFP responses by testing requested workloads.
- Build and nurture deep technical relationships with engineers, architects, and leaders at key customer accounts, and serve as a trusted advisor through application‑ and system/MLops‑focused POCs, presentations, and training.
- Engineering: 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. Compare performance to our competition.
- 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: AMD-internal guides, whitepapers, tuning guides, training collateral.
- Proactive engagement across AMD teams: GPU Business Unit, Engineering, Architecture, Platform, Software, and Product Development teams providing feedback and leadership from the field on requirements. Gathering missing functionality and working with Engineering to resolve and test.
- Assist in creating Total Cost of Ownership models to aid pricing with bid desk.
- Technically owning and resolving customer and partner issues. Submitting JIRA tickets and driving resolution.
- 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) 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.
- 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. Creating performance projections for applications.
- 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. Inspecting and dataflow down to the register-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
- This role is not eligible for visa sponsorship.
- LOCATION: Austin, TX and Remote
Qualifications
