Senior Capacity Planner

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

Anthropic’s Compute team is looking for a Senior capacity planner to lead capacity planning and forecasting of our global infrastructure fleet. You’ll work closely with research, engineering, and finance teams to model supply and demand and build capacity allocation plans that help Anthropic stay on the frontier. You’ll also ensure that engineering and model roadmaps stay aligned with the capacity plan (and vice versa) and manage execution against the plan with stakeholders across the organization.

Responsibilities:

• Design and develop a system for capacity planning that handles fast-changing AI workloads on heterogenous infrastructure
• Own source-of-truth artifacts for capacity planning with reliable actuals and weekly forecasts
• Build an in-depth understanding of research and training workloads to increase forecasting accuracy over time
• Proactively identify risks and changes to capacity needs early and work with stakeholders to find appropriate solutions
• Proactively identify efficiency opportunities and run cross-team initiatives to increase total effective compute for Anthropic
• Partner closely with senior leaders, providing detailed and clear capacity plans and inputs for decisions making

 You may be a good fit if you:

• Have experience working on capacity planning at a major cloud provider or hyperscaler company
• Have experience working with research teams
• Have familiarity with or a deep interest in learning about LLM model training and serving efficiency
• Have experience driving org-wide technical programs and collaborating with technical stakeholders
• Are comfortable navigating ambiguity and distilling uncertainty into actionable scenario planning
• Are comfortable leveraging data and making data-driven recommendations
• Have strong interpersonal skills that enable you to influence without authority and build cross-organizational support for capacity initiatives

Strong candidates may also have some of the following:

• Past experience with capacity planning for LLM model training and inference
• Past experience partnering with senior research and engineering leadership

Representative Projects:

• Build a week-by-week capacity forecast for H2 ‘25 that incorporates model training plans, inference growth, and key technical constraints
• Build a matrix for workload:model:platform support and tracker for engineering workstreams that impact capacity fungibility

Deadline to apply: None. Applications will be reviewed on a rolling basis.