Deployment Engineer, AI Inference

About Cerebras Systems

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 one device. This enables industry‑leading training and inference speeds and lets machine learning users run large‑scale ML applications without the hassle of managing hundreds of GPUs or TPUs.

Our customers include global corporations, national labs and top‑tier healthcare systems. In 2024 we launched Cerebras Inference, the fastest generative AI inference solution, over 10 times faster than GPU‑based hyperscale cloud inference services.

About The Role

We are seeking a highly skilled Deployment Engineer to build and operate cutting‑edge inference clusters on the world’s largest computer chip, the Wafer‑Scale Engine (WSE). You will play a critical role in ensuring reliable, efficient, and scalable deployment of AI inference workloads across our global infrastructure. On the operational side, you’ll own the rollout of new software versions, AI replica updates, and capacity reallocations across our custom‑built, high‑capacity datacenters. Beyond operations, you’ll drive improvements to telemetry, observability, and fully automated pipelines using advanced allocation strategies to maximize utilization of large‑scale computer fleets.

The ideal candidate combines hands‑on operation rigor with strong systems engineering skills and thrives on building resilient pipelines that keep pace with cutting‑edge AI models.

This role does not require 24 / 7 hour on‑call rotations.

Responsibilities

Deploy AI inference replicas and cluster software across multiple datacenters

Maximize capacity allocation and optimize replica placement using constraint‑solver algorithms

Operate bare‑metal inference infrastructure while supporting transition to K8S‑based platform

Develop and extend telemetry, observability and alerting solutions to ensure deployment reliability at scale

Develop and extend a fully automated deployment pipeline to support fast software updates and capacity reallocation at scale

Translate technical and customer needs into actionable requirements for the Dev Infra, Cluster, Platform and Core teams

Stay up to date with the latest advancements in AI compute infrastructure and related technologies

Skills And Requirements

2–5 years of experience operating on‑prem compute infrastructure (ideally in Machine Learning or High‑Performance Compute) or developing and managing complex AWS‑based infrastructure for hybrid deployments

Strong proficiency in Python for automation, orchestration, and deployment tooling

Solid understanding of Linux‑based systems and command‑line tools

Extensive knowledge of Docker containers and container orchestration platforms like K8S

Familiarity with spine‑leaf (Clos) networking architecture

Proficiency with telemetry and observability stacks such as Prometheus, InfluxDB and Grafana

Strong ownership mindset and accountability for complex deployments

Ability to work effectively in a fast‑paced environment

Location

SF Bay Area

Toronto

Why Join Cerebras

Build a breakthrough AI platform beyond the constraints of the GPU

Publish and open‑source 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 respects individual beliefs

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. Inclusive teams build better products and companies, and we empower people to do their best work through continuous learning, growth, and support of those around them.

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