Senior Technical Program Manager, AI Infrastructure – Capacity Operations

🕒 il y a 8 jours

🏄 California – Distant

🏄 California – Remote

💵 $168 000 - $322 000 / an

⏰ Temps Plein

🟠 Senior

🔧 Responsable de Programme Technique

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

👻 Score fantôme 1%

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NVIDIA

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1993

🏥 Santé

🏭 Fabrication

🤖 Intelligence artificielle

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA est une entreprise technologique de premier plan, spécialisée dans le calcul accéléré et l’intelligence artificielle (IA). NVIDIA est à l’avant‑garde des avancées en GPU (processeurs graphiques), cloud computing, centres de données et réalité virtuelle, avec un accent particulier sur les secteurs du gaming, de l’automobile, de la santé et de la robotique. Ses innovations, telles que NVIDIA Omniverse, transforment les processus numériques traditionnels en permettant des simulations haute fidélité et des tâches de rendu de pointe. Ses applications couvrent de nombreux secteurs, des véhicules autonomes avec NVIDIA DRIVE aux solutions de santé avec NVIDIA Clara, ainsi que des analyses et workflows pilotés par l’IA.

Description

• Own intake, triage, routing, and request-quality standards for accelerator-capacity requests across engineering and research teams • Run quarterly and annual demand forecasts, change control, review preparation, and follow-through • Prepare capacity-planning and allocation reviews using demand, supply, commitments, readiness, workload timing, and business priorities • Track capacity from request and forecast through delivery, readiness, assignment, and productive use • Coordinate infrastructure dependencies including access, storage, data movement, networking, readiness checks, migration timing, and provisioning tickets • Maintain dashboards and source-data quality, including freshness checks, reconciliation, missing-input ownership, and retirement of repeated manual reporting • Own operating cadences, agendas, action logs, dependency tracking, decision records, risk registers, blocking-issue paths, and closure • Prepare concise leadership reporting covering facts, risks, decisions, options, recommended paths, owners, and due dates • Drive tooling, automation, and decision-support initiatives with human approval gates, audit evidence, and safe operating controls • Influence research, platform engineering, infrastructure, data, finance, operations, and leadership collaborators

🎯 Exigences

• BS, MS, PhD in Electrical Engineering, Computer Science, Computer Engineering, or similar, or equivalent experience • 7+ years of technical program management or closely related experience in AI/ML platforms, distributed systems, cloud infrastructure, compute capacity, or technically demanding engineering environments • Experience owning recurring operational programs involving scarce-resource trade-offs, multiple cadences, executive clarity, and overlapping peak periods • Strong program mechanics including intake, forecasting, review preparation, dependency management, decision and risk records, action closure, documentation, and status communication • Technical proficiency sufficient to understand infrastructure constraints, inspect requirements and metrics, and work credibly with engineers and researchers • Data proficiency to evaluate source quality, interpret dashboards, reconcile conflicting views, define operational measures, and identify missing ownership • Track record transforming ambiguous cross-functional work into durable operating systems with clear owners, decisions, and critical issue paths • Excellent written and verbal communication • Ability to influence without authority across research, platform engineering, infrastructure, data, finance, operations, and leadership collaborators • Experience with GPU or accelerator-capacity planning, utilization programs, cluster operations, workload bring-up, or large-scale AI training and inference environments • Experience with demand and supply roadmaps, normalization across accelerator types, allocation reviews, quota or priority management, and capacity migrations • Familiarity with batch scheduling, cluster management, cloud, or data-center environments • Experience with observability or dashboard platforms, data-quality controls, and automated infrastructure or service-operations reporting • Experience driving API-enabled workflow automation or decision-support tools with human approval gates, audit evidence, and safe operating controls

🏖️ Avantages

• Equity • Benefits