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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.
About The Role
As an AI Infrastructure Product Manager Intern, you’ll work closely with cross-functional teams to shape strategy and execution for Cerebras’ hardware platforms. You’ll dive deep into customer needs, market dynamics, and technical tradeoffs to help guide decisions on roadmap, pricing, packaging, and positioning.
You’ll work cross-functionally with hardware engineering, software, sales, and customer success to bring category-defining inference solutions to market. If you are passionate about solving complex infrastructure challenges and building solutions that scale, this is the role for you. This internship is designed to offer real ownership and impact. You’ll present directly to senior leadership and walk away with tangible experience shipping world-class AI systems.
Responsibilities
- Drive competitive analysis and customer segmentation for Cerebras’ AI systems (CS-3, inference clusters, and beyond).
- Evaluate product-market fit for new hardware configurations and help define product packaging and pricing strategy.
- Collaborate with engineering and sales teams to gather feedback and prioritize roadmap features.
- Build business cases for new product opportunities or enhancements.
- Create internal and external collateral (e.g., product briefs, battle cards, market insights) to support go-to-market efforts.
- Present recommendations and learnings to the leadership team at the end of your internship.
Skills And Qualifications
- Currently enrolled in a full-time MBA program (Class of 2025 or 2026).
- 3+ years of prior work experience in hardware, semiconductors, AI/ML, or systems engineering.
- Strong analytical, strategic thinking, and communication skills.
- Comfortable working in fast-moving environments with ambiguity and evolving priorities.
- Technical background (e.g., BS in Electrical Engineering, Computer Engineering, or Computer Science) is strongly preferred.
Preferred Skills And Qualifications
- Experience in product management, strategy, or technical marketing roles.
- Passion for AI, high-performance compute, or ML infrastructure.
- Familiarity with hardware performance metrics, customer workloads, and industry trends in chips and systems.
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 2025.
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.
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Cerebras Systems Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cerebras Systems and has not been reviewed or approved by Cerebras Systems.
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Fair & Transparent Compensation — Pay is considered competitive for an AI‑hardware firm, and many employees are described as generally happy with compensation. Sentiment indicates compensation is viewed favorably while acknowledging variation by role and seniority.
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Healthcare Strength — Health coverage is described as top quality with medical, dental, and vision included. Premiums are reportedly fully covered for employees in some plans, increasing perceived value.
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Flexible Benefits — Work‑from‑home flexibility is regarded as strong. Flexible arrangements complement standard offerings like vacation, sick leave, and paid holidays.
Cerebras Systems Insights
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What We Do
Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art. The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2. Join us: https://cerebras.net/careers/
