US and Canada Offices
8 months ago

Job Overview

Job Type
FullTime
Pay
Not disclosed

Job description

Location:
US and Canada Offices
Work arrangement:
On-site

Role Summary

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 https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.

Responsibilities

  • Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
  • Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
  • Debug and understand runtime performance on the system and cluster.
  • Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.

Requirements

  • Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
  • Strong background in computer architecture.
  • Exposure to and understanding of low-level deep learning / LLM math.
  • Strong analytical and problem-solving mindset.
  • 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
  • Experience working on CPU/GPU simulators.
  • Exposure to performance profiling and debug on any system pipeline.
  • Comfort with C++ and Python.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

  • Build a breakthrough AI platform beyond the constraints of the GPU.
  • Publish and open source their cutting-edge AI research.
  • Work on one of the fastest AI supercomputers in the world.
  • Enjoy job stability with startup vitality.
  • Our simple, non-corporate work culture that respects individual beliefs.
  • Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!
  • Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice.

Role:
ML Systems Performance Engineer
Job Type:
FullTime

Company profile

Cerebras Systems

cerebras.ai

Cerebras Systems is an AI compute company that builds wafer-scale processors and high-speed inference systems. Its Cerebras CS-4 system, built on what it calls the biggest wafer chip, delivers up to 30x faster inference than GPUs. Organizations in medical research, cryptography, energy and agentic AI use Cerebras systems to build on-premise supercomputers, while developers and enterprises can access its technology through pay-as-you-go cloud offerings. The company was launched by Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie and Jean-Philippe Fricker, and it trades on Nasdaq under the ticker CBRS.

Company Size
500 - 1,000 employees
Headquarters
San Francisco, California, United StatesSunnyvale, California, United States
Founded
2016
Founders
Andrew Feldman
Funding Stage
Public

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