Cerebras
CoDesign & NextGen Performance Engineer
Part remote, part office, you need to live within commuting distance of a named location.
Hybrid · Sunnyvale, CA
Employer listed it 2 months ago · Added yesterday
Been open since 2 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
Not stated
Location
Hybrid · Sunnyvale, CA
Timezone
Not stated
Contract
Full-time
Experience
Mid
Category
Software
This employer didn't state pay. Jobs like this usually pay around $165k–$260k a year, a typical range taken from 595 mid-level software roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Hybrid
This role is only partly remote, the employer expects time in the office around Sunnyvale, CA, Toronto, CAN, Hybrid, so you need to live within commuting distance.
What the employer says
- Source listing states candidate location: "Sunnyvale, CA, Toronto, CAN, Hybrid"
- Listing mentions "Hybrid"
What Nomaders makes of it
- Not suitable if you plan to move between countries
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the 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.
About The Role
This role focuses on characterizing, analyzing, and optimizing the performance of state-of-the-art AI models running on Cerebras’ breakthrough hardware. You will work across the hardware and software stack to identify bottlenecks, improve computational efficiency, and help influence the design of Cerebras’ next-generation AI architecture and software systems.
Responsibilities
Bring up and optimize performance on new generations of the Cerebras WSE.
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.
Skills & Qualifications
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.
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.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, hybrid, matches where you plan to live and work.
- 2Tailor your CV to the role at Cerebras, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1d ago. Last checked 23 Sept. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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