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Senior Capacity Planner

San Francisco, CA | Seattle, WA

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. 

The expected salary range for this position is:

Annual Salary:

$365,000 - $565,000 USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process

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