AI Models, Product Manager
Confirmed live in the last 24 hours
Cerebras Systems
Job Description
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.
Own the Future of AI Inference
Cerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product — deciding which models ship, how they perform, and how the world discovers them.
You'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.
What You'll Own
Strategic Model Portfolio
- Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit
- Establish partnerships with top model labs, for day0 launches
- Build relationships with open-source maintainers to accelerate community model adoption
Product Quality & Customer Success
- Define and enforce quality standards across our model catalog through systematic evaluation frameworks
- Design benchmarks and evaluations that prove our models deliver production-grade performance
- Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering
- Enable strategic customers to integrate our inference into their products—removing blockers and optimizing for their specific use cases
Go-to-Market Excellen
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