Infrastructure Capacity Planner, Demand Planning

Anthropics 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.

Anthropics infrastructure fleet spans a growing set of clouds neoclouds and on-prem sites. Every part of it is expanding rapidly. Capacity Engineering is the team that connects every stage of that growth from capacity planning to supply management to capacity delivery to utilization. We partner on supply deals wire telemetry from day zero own the canonical capacity data layer and build the planning and enforcement tools every research and product team relies on.

As an Infrastructure Capacity Planner on the Demand Planning team youll own the medium-range demand forecast for every resource class we consume: accelerators CPU storage network and managed services. Your forecast will support sourcing and purchasing prioritization efficiency targets and workload optimization.

Key responsibilities

• Build and own the medium-range multi-resource demand forecast: accelerators by chip/interconnect class CPU by shape storage by tier and access pattern egress by path managed services by SKU driven by model roadmap RL/inference growth eval volume and retention policy rather than trend lines.
• Run the plan-vs-reality loop. Diff planned allocations against observed fleet occupancy weekly surface unrecorded trades and stale allocations and drive variance toward zero with our planning-tools and data teams.
• Qualify each incoming capacity tranche against the forecast before signature: right shape region quarter and supporting-resource envelope (storage egress CPU).
• Partner with Finance and cost-efficiency teams to turn the forecast into core drivers covering the large majority (80%) of non-accelerator spend and to aim savings work where waste will appear next.

What you bring

• Have done capacity demand or supply planning for large-scale technical infrastructure (cloud HPC hyperscale or a large internal platform) and can articulate the difference between a forecast a plan and an allocation.
• Build the model yourself rather than specifying it for someone else: SQL against a warehouse Python/pandas or a proper forecasting/optimization stack.
• Understand data-center resource classes well to know why storage and egress dont forecast like GPUs and why a contracts headline chip count is rarely the binding constraint.
• Prefer simple inspectable models to clever opaque ones and instrument your own forecast error.

Preferred qualifications

• Direct experience with cloud or neocloud providers on reserved-capacity onboarding private offers or capacity commitments.
• Demand planning or forecasting experience for accelerator fleets including translating research or product roadmaps into resource requirements.
• Data center or colocation delivery experience: power and space planning network turn-up site acceptance criteria and vendor management.
• Experience with accelerator health and burn-in collective-communications sanity testing or fleet-health SLOs and the ability to define healthy rigorously.
• Experience building lifecycle or state-machine services or systems of record for infrastructure assets.
• Experience onboarding a new hardware generation into an existing scheduler and observability stack.

Minimum education: Bachelors degree or an equivalent combination of education training and/or experience

Required field of study:A field relevant to the role as demonstrated through coursework training or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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 arent 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 youre interested in this work. We think AI systems like the ones were 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.

Your safety matters to us. To protect yourself from potential scams remember that Anthropic recruiters only contact you some cases we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money fees or banking information before your first day. If youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

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. Were 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.

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 aboutour policy for using AI in our application process.