Cerebras Systems

Cerebras Systems

Power Engineering Architect

Sunnyvale, CA · Senior

Sponsorship not specified$230k-$275kDetected 2 days ago
Machine LearningComplianceThermal AnalysisPCB Design

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odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level IV · 4×
Level I$130,6861 entry
Level II$159,8902 entries
Level III$189,0723 entries
Level IV$218,2754 entries

This range already reaches Level IV — the maximum four lottery entries.

DOL prevailing wage, 2026-27 wage year · Electrical Engineers (17-2071) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

22 transfer filings in the last year, covering 22 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • 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.
  • 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.

Responsibilities

  • Lead system architecture exploration with a focus on power delivery and thermal management.
  • Drive innovation in vertical power delivery to the wafer, enabling ultra-high current density solutions.
  • Collaborate with internal product, ASIC, and systems teams to define and refine detailed power specifications.
  • Evaluate and select optimal architectures and strategic partners/vendors for new technology development.
  • Collaborate with package, silicon, PCB, and mechanical to optimize power delivery
  • Strong foundation in energy-efficient system design and associated trade-offs.

Requirements

  • 15+ years of hands-on experience in power delivery systems.
  • Practical experience in thermal modeling and cooling solution implementation.
  • Experience with multiphase buck regulators, digital power controllers, DrMOS, smart power stages, and integrated voltage regulators
  • Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc.
  • MSEE or MSCE required

Nice to have

  • Solid background in semiconductor technologies, including PMICs and integrated power modules.
  • Why Join Cerebras
  • 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:
  • 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.

Skills

  • Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups.

Compensation

  • The base salary range for this position is $230,000 to $275,000+ annually.

Company info

  • Build a breakthrough AI platform beyond the constraints of the GPU.
  • Our simple, non-corporate work culture that respects individual beliefs.

This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.