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Cerebras

AI accelerator hardware replacing GPUs

Engineering Lead - Kernel Reliability

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSunnyvale, CA, USANo salary listedHybrid

About the Job

Requirements

  • At least 6 years of software engineering experience, including 3+ years leading teams in software or hardware reliability, debugging, diagnostics, failure analysis, or related fields.
  • Expertise in parallel and distributed programming, including message passing, multicore, GPU, or embedded environments.
  • Experience developing or using debugging and diagnostic tools, including debuggers, core dump handling, and code sanitizers.
  • Experience debugging distributed and parallel applications, including deadlocks, livelocks, and race conditions.
  • Deep understanding of computer architectures, including instruction pipelining, multithreading, and networking.
  • Strong background in operations and monitoring, including incident response and post-mortem analysis.
  • Demonstrated ability to recruit and retain high-performing teams and partner cross-functionally to deliver customer-facing products.

Responsibilities

  • Provide hands-on technical leadership and own the technical vision and roadmap for kernel-centric reliability of internal and customer-facing systems.
  • Assist System and Cluster Operations teams in reducing system and service downtime after failures by providing tooling and manual intervention for failure analysis and diagnostics.
  • Work with the Debug Team to enhance debugging tools and speed up failure analysis.
  • Collaborate with software teams to improve the software stack, including kernels, for on-field debugging and failure analysis.
  • Work with ASIC and hardware architecture teams to co-design next-generation architectures with reliability and ease of debugging in mind.
  • Lead, mentor, and grow a team of engineers, fostering technical excellence and rapid execution.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

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