Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top 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.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.
About The Role
Join our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.
Skills & Qualifications
- 10+ years of physical design & physical verification experience.
- Strong knowledge of block level and full-chip physical verification methodology.
- Strong experience in block/subsystem timing closure.
- Expert at optimizing for the best power/performance and area.
- Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.
- Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
- Expert with IR/EM analysis and resolution.
- Good understanding of full chip floor planning and integration.
- Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
- Demonstrated ability to work with RTL teams to optimize for physical design.
- Knowledge of CPU/GPU design a plus.
- Skills in Design Compiler, Fusion Compiler, ICC2 or similar physical design tools.
- BS or MS in Electrical Engineering.
The salary range for this position is $150,000 – $250,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
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.
Read our blog: Five Reasons to Join Cerebras in 2026.
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 to review our CCPA disclosure notice.
Similar Jobs
What you need to know about the Los Angeles Tech Scene
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
