AI Infrastructure Operations Engineer

About the role

We are seeking a highly skilled and experienced AI Infrastructure Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power. You will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success.

Responsibilities

• Manage and operate multiple advanced AI compute infrastructure clusters.
• Monitor and oversee cluster health, proactively identifying and resolving potential issues.
• Maximize compute capacity through optimization and efficient resource allocation.
• Deploy, configure, and debug container-based services using Docker.
• Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed.
• Handle engineering escalations and collaborate with other teams to resolve complex technical challenges.
• Contribute to the development and improvement of our monitoring and support processes.
• Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies.
• Skills And Requirements
• 6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing.
• Strong proficiency in Python scripting for automation and system administration.
• Deep understanding of Linux-based compute systems and command-line tools.
• Extensive knowledge of Docker containers and container orchestration platforms like k8s and SLURM.
• Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner.
• Experience with monitoring and alerting systems.
• Should have a proven track record to own and drive challenges to completion.
• Excellent communication and collaboration skills.
• Ability to work effectively in a fast-paced environment.
• Willingness to participate in a 24/7 on-call rotation.
• Preferred Skills And Requirements
• Operating large scale GPU clusters.
• Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired.
• Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure).
• Familiarity with machine learning frameworks and tools.
• Experience with cross-functional team projects.
• Location
• SF Bay Area.
• Toronto, Canada.
• Bangalore, India.
• Why Join 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 2026.
• 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 i

Benefits

Additional Information

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.

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