Graphcore

Artificial Intelligence

AIPlatformArchitect

Austin, Texas, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“AI Platform Architect at Graphcore. Skills: AI Platform Architecture, Distributed AI Workloads, Hardware-Software Co-design. Design holistic architecture. Influence AI workload scheduling”

What You'll Achieve.

ensure our AI research and deployment teams have a flawless, frictionless, and extraordinarily powerful platform

Industry & Context.

Artificial Intelligence
Problems you'll solve

eliminate system-level bottlenecks

What They're Looking For.

Must Have

systems engineering, cloud architecture, HPC, hardware engineering, distributed AI frameworks, data parallelism, tensor parallelism, pipeline parallelism, LLM architectures, system-level bottlenecks, data pathways, container orchestration platforms, infrastructure-as-code, GPU-heavy bare-metal, cloud environments, AI researchers, data scientists, low-level hardware, CPU, memory, storage, GPU, network engineers, model requirements, infrastructure specifications, Platform engineering requirement specifications

Nice to Have

Rack scale GPU AI Platforms experience, Python, JSON, Neural engine silicon solutions

What You'll Do.

Design holistic architecture

Influence AI workload scheduling

Manage distributed training jobs

Profile system-level bottlenecks

Tune deep learning frameworks

Work closely with engineering

Influence platform design

Drive technical vision

Collaborate with subject matter experts

Define requirements specifications

Communicate and present

Define board routing guidelines

Define thermal targets

Define feeds and speeds

Perform market competitive analysis

How You'll Work.

Team & Collaboration

Work closely with software, firmware, and OS engineering; Collaborate closely with subject matter experts; Communicate and present to internal and external silicon teams; Bridge the gap between AI researchers/data scientists and low-level hardware/CPU/memory/storage/GPU/network engineers

Communication Scope

Ability to communicate and present to internal and external silicon teams

Full Job Description

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking for a visionary AI Platform Architect to design and oversee the comprehensive infrastructure stack that powers our most demanding distributed AI workloads. Moving beyond individual hardware components, this role acts as the unifying technical authority across hardware, software, compute, network, and storage. You will be responsible for architecting a cohesive, AI rack scale platform optimized for trillion-parameter LLM training and high-throughput inference. By orchestrating everything from advanced clustering and distributed training frameworks down to the physical layer—spanning PCIe Gen 5/6 pathways, NVMe storage topologies, and RDMA fabrics—you will ensure our AI research and deployment teams have a flawless, frictionless, and extraordinarily powerful platform at their disposal. Responsibilities and Duties End-to-End Platform Architecture: Define the holistic architecture for highly clustered AI environments, ensuring zero-bottleneck data flow between parallel storage systems, AI compute nodes, and ultra-high-bandwidth network fabrics. Workload Orchestration: Influence the strategy for AI worklo

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