Research

Quality Assurance

Program and Project Management

Entrepreneurship

Engineering

Business Development

Product Management

Operations

Information Technology

Human Resources

Founder and CEO

Chief Financial Officer

Sources: AI chipmaker Cerebras confidentially files for a US IPO after withdrawing a previous IPO last year, and a listing could take place as soon as April (The Information)

Abu Dhabi's G42 and MBZUAI join US firm Cerebras to build AI supercomputer in India

UAE to deploy 8 exaflop supercomputer in India

Startup news and updates: daily roundup (February 20, 2026)

Kernel Engineer

Cerebras Systems builds the world's largest AI chip, and they are seeking a Kernel Engineer to develop high-performance software solutions for AI and HPC workloads. The role focuses on implementing, optimizing, and scaling deep learning operations to leverage their custom processor architecture, as well as building a library of parallel and distributed algorithms.

Deployment Engineer, AI Inference

Cerebras Systems builds the world's largest AI chip, providing leading training and inference speeds for machine learning applications. The Deployment Engineer will be responsible for building and operating inference clusters and ensuring the reliable deployment of AI workloads across a global infrastructure.

CoDesign & NextGen - New College Grad

Cerebras Systems builds the world's largest AI chip, providing unprecedented AI compute power with their novel wafer-scale architecture. The CoDesign and NextGen engineers will work at the interface of software and hardware, focusing on kernel design, ASIC performance modeling, and system robustness.

Inference Frontend

Cerebras Systems builds the world's largest AI chip, providing unmatched AI compute power. The Inference Frontend role involves collaborating with engineers to design and implement software solutions that enhance system performance and usability.

Product Manager, Strategic Verticals

Cerebras Systems builds the world's largest AI chip, providing cutting-edge AI compute power for large-scale ML applications. The Product Manager for Strategic Verticals will lead customer engagement and solution design, ensuring successful AI implementations for both startups and Fortune 500 companies.

System Software Engineer (Embedded)

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. The role involves developing administrative software for the Cerebras Wafer Scale Engine, collaborating with hardware teams, and enhancing system reliability and maintainability across the embedded stack.

Cerebras Systems is a leading company in AI technology, renowned for building the world's largest AI chip. The role of System Software Engineer (Embedded) involves developing software that powers the Cerebras Wafer Scale Engine, ensuring reliable operation at scale and collaborating with cross-functional teams to enhance system performance.

Engineering Manager, Kernel Reliability

Cerebras Systems builds the world's largest AI chip and is looking for a deeply technical, hands-on engineering leader for their Kernel Reliability team. The role involves leading a team to improve the reliability of advanced compute clusters and internal production services, while setting the technical vision and collaborating with various teams to enhance system performance.

Senior Full Stack LLM Engineer - Training

Cerebras Systems builds the world's largest AI chip, and they are seeking a versatile and experienced engineer to join their SOTA Training Platform team. This role involves rapidly bringing up state-of-the-art open-source and proprietary models on Cerebras CSX systems, contributing to performance, efficiency, and scalability for AI applications.

LLM Inference Performance & Evals Engineer

Cerebras Systems builds the world's largest AI chip, revolutionizing AI compute power with its unique wafer-scale architecture. The LLM Inference Performance & Evals Engineer will join the inference model team to prototype and benchmark cutting-edge ideas, develop automation for experiments, and collaborate across software and hardware teams to optimize performance.