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Principal Hardware Diagnostics Engineer
Graphcore — лидер в области ИИ-вычислений, а статус части SoftBank Group обеспечивает стабильность и масштаб. Позиция предлагает работу с передовыми технологиями и высокий уровень влияния на продукт.
Сложность вакансии
Роль уровня Principal требует глубоких знаний на стыке софта и железа, опыта работы с гиперскейлерами и умения проектировать сложные системы диагностики для ИИ-кластеров. Высокая планка ответственности за стабильность систем мирового уровня.
Анализ зарплаты
Указанный диапазон соответствует рыночным стандартам для позиций уровня Principal в Кремниевой долине (Милпитас), где базовые зарплаты в ИИ-секторе начинаются от $200k и дополняются значительными пакетами акций.
Сопроводительное письмо
I am writing to express my strong interest in the Principal Hardware Diagnostics Engineer position at Graphcore. With extensive experience in developing diagnostic software for high-performance hardware and a deep understanding of system-level monitoring, I am eager to contribute to the reliability and scalability of your next-generation AI compute platforms. My background in architecting diagnostic agents and collaborating with ODM partners aligns perfectly with Graphcore's mission to deliver robust AI infrastructure.
Throughout my career, I have specialized in building automated diagnostics solutions that bridge the gap between low-level hardware telemetry and high-level cloud infrastructure. I am particularly drawn to Graphcore's innovative culture and the opportunity to work on rack-scale AI systems within the SoftBank Group ecosystem. I am confident that my expertise in Python/C++ and my experience with distributed systems will allow me to make an immediate impact on your Systems Engineering and Platform Validation team.
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Описание вакансии
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 an experienced Principal Hardware Diagnostics Engineer to design and develop diagnostics software used to monitor hardware health and diagnose system-level issues across Graphcore’s AI infrastructure platforms.
This role focuses on building diagnostics agents, tools, and analytics frameworks that enable engineers and automation systems to identify, isolate, and resolve hardware issues across blade-level servers and rack-scale clusters.
The Team
Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption.
The Systems Engineering and Platform Validation team ensures Graphcore’s AI compute platforms are reliable, diagnosable, and operationally robust at scale.
The team collaborates with hardware engineering, firmware, cloud infrastructure, and automation teams to develop tools and frameworks that monitor system health, detect hardware failures, and accelerate root-cause analysis across AI clusters.
Responsibilities and Duties
- Design and develop automated hardware diagnostics solutions for blade-level servers and rack-scale AI systems.
- Architect and implement diagnostic agents, monitoring tools, and analytics frameworks to track hardware telemetry.
- Collaborate with hardware teams to integrate low-level diagnostic modules into monitoring systems.
- Develop diagnostics tools capable of detecting hardware health conditions and isolating failures.
- Create diagnostic modules used for internal validation and production data center operations.
- Provide detailed hardware fault information to system engineers to accelerate troubleshooting.
- Define remediation workflows and insights for hardware fault scenarios across nodes and clusters.
- Collaborate with firmware, networking, and cloud platform teams to integrate diagnostics across the system stack.
Candidate Profile
Essential
- Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or related discipline.
- Strong software engineering experience in Python, C++, or C#.
- Experience developing diagnostics or monitoring systems for hardware platforms.
- Experience working with distributed systems or cloud infrastructure.
- Strong knowledge of Linux environments and system-level diagnostics tools.
- Experience collaborating with CM/ODM partners on manufacturing diagnostics and fault isolation.
- Strong analytical and debugging skills.
- Excellent communication and collaboration abilities.
Desirable
- Experience working with AI hardware platforms or accelerator-based computing systems.
- Familiarity with hyperscale data center infrastructure.
- Experience building cluster-level monitoring or diagnostics systems.
- Experience interacting with internal or external customers during diagnostics solution development.
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Навыки
- Python
- C++
- Linux
- Distributed Systems
- Hardware Diagnostics
- Cloud Infrastructure
- System Debugging
- AI Hardware
Возможные вопросы на собеседовании
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Расскажите о вашем опыте работы с CM/ODM партнерами при внедрении производственной диагностики. С какими трудностями вы сталкивались?
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Как вы подходите к изоляции 'плавающих' (intermittent) аппаратных ошибок в распределенной среде?
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Как бы вы спроектировали автоматизированный рабочий процесс (remediation workflow) после обнаружения критической ошибки памяти в стойке?
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