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GPU Architect

Graphcore · US - Milpitas · Active · Greenhouse

Job facts

FieldValue
CompanyGraphcore
TitleGPU Architect
Normalized title-
Department / teamAdvanced Architecture
LocationUnited States
Work model-
Employment type-
Salary-
Statusactive
ATS providerGreenhouse
Posted / first seen2026-06-01 / 2026-06-02
Changed / last seen2026-06-02 / 2026-06-06

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Company jobsActive postings from Graphcore.Open
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ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Advanced Architecture.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyGraphcore
Source8cf2ee21-6ab4-4155-95e7-a37f92d8e9f7
ATS providerGreenhouse

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. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing!. 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 a highly accomplished experienced GPU Architect to define the next generation of AI accelerators and multi-GPU cluster architecture. As the demand for trillion-parameter LLM training and high-throughput localized inference accelerates, the role of GPU architecture has never been more critical. In this role, you will lead the technology characterization, reliability, and interconnect performance strategies that ensure our compute fabrics scale flawlessly. You will collaborate deeply across hardware, firmware, and AI silicon teams to build GPU infrastructure capable of pushing the absolute limits of parallel processing and hardware efficiency. Responsibilities and Duties Hardware-Software Co-Design: Collaborate with software engineering to ensure the AI compute and Rack level hardware architectures fundamentally accelerate lower-level ML frameworks and localized inference engines (e.g., vLLM, Ollama, TensorRT). Performance Modeling: Build and analyze cycle-accurate simulators and analytical models to identify bottlenecks, forecast workload performance, and guide architectural trade-offs. Influence long-term silicon architecture roadmaps with our GPU SoC teams. Mentor engineering teams and drive strict engineering standards from feasibility to tape-out and post-silicon validation. Reliability: As a Platform level GPU architect, the role requires the candidate to have extensive knowledge in Reliability and Quality including but not limited to the ability to calculate MTBF, FIT rates, IEFR, IFR, and lifecycle bath-tub curves to understand repair rates, SLAs, uptime curves. NPI Manufacturing: The role requires a deep knowledge with manufacturing processes to detect and correct any inadequate manufacturing frameworks that can impact the overall quality of the products we deploy in our Datacenters. Candidate Profile Essential: Experience: 10+ years of deep experience in GPUs, AI accelerators, or highly parallel computer systems in areas of qualification, manufacturing, and programming. Microarchitecture Expertise: Understanding of SIMD/SIMT execution models, instruction scheduling, and hardware acceleration for machine learning algorithms. Manufacturing: Deep knowledge of advanced manufacturing techniques for build of AI compute units and Rack level L11 liquid cooled solutions. Systems Interconnects: Extensive hands-on experience characterizing data pathways across RDMA environments, and hardware clustering protocols. Programming & Tooling: Proficiency in C++, Python, or similar languages for performance modeling, GPU technology characterization, and workload profiling. Analytical Rigor: Exceptional ability to characterize complex AI mathematical operations into efficient hardware implementations. Education: BS or MS or equivalent experience in Computer Engineering or Electrical Engineering. Desirable Specific Topology Experience: Direct experience qualifying Rack-scale GPU designs including but not limited to NPI manufacturing, testing, quality and reliability calculations. We welcome people of different backgrounds and experiences and are committed to building an inclusive work environment that makes Graphcore a great home for everyone. We are an equal opportunity employer and want to build a work environment where everyone is happy, productive and respectful so they can do their best work. If you have a disability or additional need that requires accommodation, just let us know.

Full job record

Job IDf9a712c96a5876acb5213ee413abe3d8ae2f9c50
Org ID6cda449c-a757-492f-84f5-c7ddfb69f3c9
Source ID8cf2ee21-6ab4-4155-95e7-a37f92d8e9f7
Board ID8cf2ee21-6ab4-4155-95e7-a37f92d8e9f7
Providergreenhouse
Provider Job Key8562938002
TitleGPU Architect
Normalized Title
Statusactive
Activeyes
Location TextUS - Milpitas
DepartmentAdvanced Architecture
Team
Employment Type
Workplace Type
Remote Policy
CountryUnited States
Region
City
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://job-boards.greenhouse.io/graphcore/jobs/8562938002
Apply URLhttps://job-boards.greenhouse.io/graphcore/jobs/8562938002
First Seen At2026-06-02 12:08:21Z
Last Seen At2026-06-06 07:33:58Z
Last Checked At2026-06-06 07:33:58Z
Last Changed At2026-06-02 12:08:21Z
Inactive At
Source Posted At2026-06-01 13:35:09Z
Source Updated At2026-06-01 13:35:09Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=graphcore/date=2026-06-06/2026-06-06T07-33-58-066Z-c45ac7c3287745423a5e9032eef4364933a2d95b7e4907e84e67134355260519.json
Event Fields
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Extensions
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