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Cerebras is looking for an experienced Technical Program Manager to drive capacity planning and fleet strategy for its AI inference service. You will work closely with engineering and product teams to ensure optimal utilization of cutting-edge AI capabilities.
Responsibilities include managing capacity forecasts, supporting datacenter operations, and enhancing internal tools. The ideal candidate will have extensive experience in cloud infrastructure and large-scale ML.
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; 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.
Cerebras works with the leading 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.
As demand for AI continues to accelerate, intelligent capacity management becomes one of the company's most strategic challenges. Every customer commitment, model launch, and infrastructure investment depends on making the right capacity decisions at the right time. We are looking for an experienced Technical Program Manager to lead capacity planning and fleet strategy for our Inference Service organization. This is a highly visible role working directly with Engineering, Product, Infrastructure, SRE, Operations, and executive leadership to maximize utilization of one of the world's most advanced AI inference fleets.
Capacity planning and forecasting. Build and maintain the 6/12/26-week rolling capacity model across every cluster. Work with product team to translate customer contracts and sales pipeline asks into capacity requirements. Forecast model replicas, system-hours, and spares by customer and by model. Reconcile against actuals weekly. Maintain the source-of-truth doc.
New Datacenter Capacity bring‑up. Collaborate with datacenter infrastructure and operations teams to support new datacenter bring‑up and ensure production readiness. Drive engineering efforts and related automation to ensure on‑time and quality delivery.
Allocation and cluster placement. Partner closely with the SRE and product team to run the weekly capacity review across different customers/models/clusters. Decide model placement and re‑balancing: which customer tenants land where, which clusters absorb new launches, which freezes are in effect, etc. Run the weekly capacity and utilization report for the Inference Service leadership. Post capacity allocation, drive downstream tasks with respect to deploying models across the allocated capacity with the SRE team.
Drive capacity planning tool adoption. Partner with console engineering team to drive stakeholder adoption of the inhouse built capacity planning and allocation tool, including user acceptance testing, issue resolution, tracking changes, pilot testing and deployment. In general, contribute to the continuous process improvement and development of internal capacity management tools.
Incident tracking and postmortems. Proactively identify and mitigate capacity bottlenecks, risks, and dependencies. In case of any SLA drop due to capacity misallocations, drive related resolution and postmortem.
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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