Cerebras Systems
Sr. Member of Technical Staff
Sunnyvale, CA · Staff+
Sponsorship not specifiedDetected 74 days ago
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About the role
- 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.
- 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.
Responsibilities
- People who are serious about software make their own hardware.
- Build a breakthrough AI platform beyond the constraints of the GPU.
- We believe inclusive teams build better products and companies.
Requirements
- Master's degree or foreign equivalent degree in Computer Science, or a related field and 18 months of experience as Information Security Analyst, Software Engineer, Sr.
- Member of Technical Staff, IT Senior Applications Engineer, or a related occupation required.
- The required experience must include 18 months of experience with the following:
Skills
- Cerebras Systems Inc. has multiple openings for Sr.
- Member of Technical Staff
Compensation
- $230,000.00 per year to $250,000.00 per year
Benefits
- 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.
Company info
- 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.
Equal opportunity
- Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer.
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This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.