AI Compute Infrastructure Engineer

Cerebras Systems has pioneered a groundbreaking chip and system that revolutionizes deep learning applications. Our system empowers ML researchers to achieve unprecedented speeds in training and inference workloads, propelling AI innovation to new horizons. 

Condor Galaxy 1 (CG-1), a supercomputer set to revolutionize the world of artificial intelligence. With an astounding processing power of 4 ExaFLOPs, 54 million cores, and a cutting-edge 64-node architecture, the CG-1 is the first milestone of a larger project that will redefine the possibilities of AI. 

The successful completion and deployment of the CG-1, the first of nine powerful supercomputers, is a significant achievement for Cerebras. As we enter phase 2 of the project with CG2, we are taking a bold step towards creating a network of interconnected supercomputers that will collectively deliver a mind-boggling 36 ExaFLOPs of AI compute power upon completion.  

Responsibilities

• Operate and manage multiple Advanced ML accelerator solutions from Cerebras Systems – Condor Galaxy
• Maximize the available compute capacity – thereby providing high uptime at max performance for the CG deployments
• Monitor and oversee CG health to ensure stability and security
• Manage and customize k8s, cluster, cloud features on CGs
• Provide solutions to ML users using tools and components available in a vast linux-based ecosystem – compute, storage, networking. 
• Configure, deploy and debug container-based services on orchestration platforms like Kubernetes.
• Provide 24/7 monitoring, support – using automated tools and hands-on manual troubleshooting
• Training and Inference in data center, LLM (50b to 500b parameter models),  multi-modal, mistral etc.
• Adapt and make progress in a fast-paced and constantly evolving environment.
• Document processes and procedures needed to efficiently operate CGs.

Requirements

• BS CS/EE, MS CS/EE
• 5+ years relevant experience in managing compute infrastructure
• Hands-on technical expert
• Proficiency with Python and other common programming languages
• Demonstrated high impact in a variety of products and roles
• Experience in container orchestration platforms like Kubernetes and SLURM
• Experience with ML frameworks like PyTorch, Tensorflow, etc.
• Strong knowledge and demonstrated experience with:
• Linux based compute systems, virtualization, docker containers
• Scheduling and orchestration applications like SLURM, Kubernetes
• Good understanding of cloud infrastructure design, deployment and maintenance
• Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired
• Past experience with cross-functional team projects
• Past experience and interactions with high-value customers
• Should have a proven track record to own and drive challenges to completion

Location 

• SF Bay Area 

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:

1. Build a breakthrough AI platform beyond the constraints of the GPU
2. Publish and open source their cutting-edge AI research
3. Work on one of the fastest AI supercomputers in the world
4. Enjoy job stability with startup vitality
5. Our simple, non-corporate work culture that respects individual beliefs

Read our blog: Five Reasons to Join Cerebras in 2024.

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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