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Principal Capacity Engineer, Compute

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 Principal Capacity Engineer to lead capacity planning, forecasting, and optimizing of our global infrastructure fleet. You’ll work closely with research, engineering, and finance teams to ensure we have scalable systems for capacity management, high-quality data and insights for planning, and engineering roadmaps that deliver efficiency wins and increase total effective compute. Experience with capacity management for AI workloads is preferred.

Responsibilities:

  • Design, develop, and deliver capacity management systems for AI workloads on heterogenous infrastructure
  • Build and maintain robust attribution of usage and enable in-depth data-driven insights
  • Oversee design and implementation of planning tools and systems-level guardrails for capacity planning and quota management
  • Build a deep understanding of research and training workloads to accurately model cost-to-serve and cost-to-train
  • Proactively identify efficiency opportunities and collaborate with teams across the org to increase total effective compute for Anthropic
  • Partner closely with Finance and leadership, providing detailed and clear capacity inputs for financial planning and strategic decision making

 You may be a good fit if you:

  • Have experience working on capacity at a major cloud provider or hyperscaler company
  • Have experience driving cross-functional projects and interfacing with technical and non-technical stakeholders.
  • Have experience working with LLMs and/or a deep interest in learning about model training and serving efficiency
  • Are comfortable leveraging data and have experience building observability for complex systems
  • 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 as a lead capacity engineer
  • Past experience partnering with senior leadership
  • Past experience working on model training or model inference

Representative Projects:

  • Building a system for capacity planning and optimizing resource allocation for model training, inference, and research

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

The expected salary range for this position is:

Annual Salary:

$435,000 - $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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