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

The Inference Core Platform group is at the heart of Cerebras' mission to deliver the world’s fastest AI inference. Our team builds the foundational software and hardware infrastructure that powers low-latency, high-speed, high-throughput deployment on the Cerebras Wafer-Scale Engine (WSE). We are responsible for the full stack—from model compilation and scheduling down to custom hardware kernels and driver development.

We operate at the intersection of cutting-edge AI research and systems engineering, with a relentless focus on performance, scalability, and reliability. We are looking for engineers to help shape the future of AI inference and work on one of the most ambitious computing systems ever built.

Scope of Inference Core Platform Team includes:

• Model Compiler Stack – Transforming and optimizing large-scale models for efficient execution on the WSE.
• Software Drivers & Hardware Kernels – Delivering low-level performance-critical components that interface directly with the Cerebras hardware.
• Schedulers – Managing compute and memory resources to maximize throughput and minimize latency across dynamic inference workloads.
• Core Inference Features – Developing and scaling state-of-the-art capabilities such as speculative decoding, dynamic batching, prompt caching, quantization-aware execution, and more.
• Debug and Profiling Tools – Creating visibility into performance and correctness to enable rapid iteration and deployment at scale.

Skills And Preferred Qualifications

• Bachelor’s, Master’s, Computer Engineering, Systems Engineering, or a related field.
• Proven experience in low level systems integration and problem solving at the intersection of hardware and software.
• Strong background in throughput and performance optimization techniques, particularly those involving hard problems.
• Proficiency in Python or C++ programming.
• Acumen to dive deep and new domains.
• Familiarity with AI workloads and architectures is a plus.
• Excellent problem-solving skills and a strong analytical mindset.
• Ability to work in a fast-paced, ambiguous, and collaborative environment.

What We Offer

• Competitive salary and benefits package.
• Opportunities for professional growth and career advancement.
• A dynamic and innovative work environment.
• The chance to work on cutting-edge technologies and make a significant impact on the future of AI.

Why Join Cerebras

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.