Startups · AI

ML Systems Integration Engineer

Cerebras Systems · Sunnyvale, CA · Remote

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About Cerebras Systems

Cerebras powers the world's fastest AI inference on the biggest wafer chip. Cerebras CS-4 delivers up to 30x faster inference than GPUs.

About the role

Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure. Debug complex system-level issues spanning hardware and software interactions.

What they're looking for

  • BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field
  • Strong programming skills in Python and/or C++
  • Excellent debugging and problem-solving skills with ability to investigate complex technical issues methodically
  • Solid understanding of operating systems fundamentals (processes, threads, memory management, concurrency, IPC)
  • Experience working in Linux development environments
  • Understanding of computer architecture and interactions between hardware and software systems
More about this role

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure.

Debug complex system-level issues spanning hardware and software interactions.

Investigate failures occurring during system bring-up and identify root causes using logs, telemetry, and diagnostic tools.

Build automation frameworks and internal tooling that improve system validation and debugging workflows.

Develop software used to test, validate, and stress distributed hardware systems during...

Read the full posting on Cerebras Systems's site ↗

Software Engineering

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