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Vacantes / Anthropic

Infrastructure Capacity Planner, Demand Planning

Anthropic · San Francisco, CA | New York City, NYmid

En corto

  • ▸Planner de capacidad de infraestructura que pronostica demanda de recursos técnicos (GPU, CPU, almacenamiento, etc.)
  • ▸Trabajas con datos reales y herramientas para comparar planes con resultados, corrigiendo desviaciones semanales
  • ▸El gran diferenciador: tu pronóstico alimenta compras, priorizaciones y ahorros en más del 80% del gasto no-acelerador

Fluency in English required

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En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

¿Qué piden?

  • ✓Experiencia en planificación de capacidad en infraestructura técnica a gran escala (nube, HPC, hyperscale)
  • ✓Capacidad de construir modelos de pronóstico con SQL, Python/pandas o herramientas de optimización
  • ✓Conocimiento profundo de clases de recursos de centro de datos (GPU, almacenamiento, red, etc.)
  • ✓Capacidad para diferenciar pronóstico, plan y asignación
  • ✓Habilidades para evaluar tranches de capacidad antes de firmar contratos
  • ✓Capacidad de trabajar con equipos de finanzas y eficiencia para convertir pronósticos en drivers de ahorro

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

SQLPythonpandasforecasting stackoptimization stackdata warehousetelemetryplanning-toolsdata teamssourcing teams

¿A quién escribirle en Anthropic?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

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 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, you'll 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 don't forecast like GPUs, and why a contract's 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. The annual compensation range for this role is li

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