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We are seeking a Senior Field Application Engineer (FAE) to join the Centre of Excellence (CoE) to lead the AI discussion and demonstration within the worlds largest national labs and sovereign AI centres. The role broadly involves; Providing technical AI positioning and Proof of Concepts for AI factories, Gigafactories and other Sovereign AI customers at both application and systems level; ‘Hands-on’ engineering investigations to understand both performance and characteristic performance across popular and customer-specific training and inference workloads; Owning the technical interface into the customer and qualification. Working closely with sales and partners to position AMD solutions. Understanding concerns and blockers; Positioning AMD Instinct GPUs, EPYC CPUs and our new ‘AI smart NICs’
Job Responsibility:
Support winning new AI business in national AI and HPC centres. Enabling customers to execute their AI workloads on AMD Instinct GPUs, EPYC CPUs, and AI NICs. Supporting partners in RFP responses by testing requested workloads
Owning technical qualification of the customer, partnering with Sales and Business Unit orgs
Demonstrate and advise customers and partners through Proof of Concepts, 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
Provide onsite training
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
Requirements:
Demonstrable hands-on expertise working with either popular AI frameworks and models on GPU
Experience leading large technical programs or opportunities
Strong systems background. Understands and can quantify the impact of system architecture on performance
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
Based in Europe ideally EU zone
Open to travel both domestic and international, approximately 10-20% over a year. Anticipate a ramp period with increased travel at the start
Bachelors' Degree in a technical field (Computer Science, Electrical Engineering, Physics, Mathematics) preferred
Nice to have:
Hands-on AI and HPC experience within large national HPC centres
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