Finance Manager – Infrastructure, Capacity

Job not on LinkedIn

🔥 12 hours ago

🇺🇸 United States – Remote

💵 $140k - $180k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

💸 Financial Planning and Analysis (FP&A)

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Runpod

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

💰 $20M Seed on 2024-06

Artificial Intelligence • SaaS • B2B

Runpod is a cloud platform that provides on-demand GPU compute and managed infrastructure tailored for AI development and deployment. It offers GPU "Pods" across 31 global regions, serverless GPU endpoints for low-latency inference, multi-node GPU clusters for distributed training, and a hub for deploying open-source models and templates. Runpod emphasizes fast startup (sub-200ms cold starts), autoscaling from zero to thousands of workers, support for 30+ GPU SKUs, and tooling for the full AI lifecycle from experiment to production, targeting developers and enterprise AI teams.

📋 Description

• Maintain a live view of available capacity across GPU types and datacenters • Serve as the company's source of truth for available, sold, and upcoming capacity • Drive fill on upcoming capacity tranches with Sales and Infrastructure • Monitor fleet utilization and address underperforming SKUs, datacenters, and node groups • Evaluate GPU ownership models including revenue share, leasing, and direct purchase • Forecast cash requirements and own the capacity capex plan • Model revenue impact of bring-up timing and quantify delay costs • Evaluate and monitor non-GPU infrastructure investments, including storage and CPU capacity • Build fleet unit economics, including contribution margin by GPU type, datacenter, and host • Set pricing floors and return hurdles for capacity decisions • Support commercial negotiations with hosts and datacenter partners • Model term sheets, revenue-share splits, and lease economics • Run scenario and risk analysis on the supply book • Own capacity reporting dashboards and post-commitment variance analysis • Report to Runpod's Director of Finance and partner with Infrastructure, Data Center Operations, and Sales

🎯 Requirements

• 4+ years of experience in finance, FP&A, corporate development, or a related analytical role • Strong foundation in financial modeling and forecasting • Advanced proficiency in Excel/Google Sheets modeling, including capex, cash flow, and return analysis (NPV, IRR, payback) • Comfort working with large operational datasets and BI tools • Comfort driving ambiguous initiatives to completion with minimal supervision • Strong negotiation and communication skills, with the ability to translate data into clear recommendations for business stakeholders • Successful completion of a background check • Experience in a high-growth startup or venture-backed technology company preferred • Experience underwriting capital-intensive investments preferred • Experience with lease-versus-buy analysis, equipment financing, or revenue-share structures preferred • Experience in capacity, supply, or fleet planning preferred • SQL or hands-on experience querying large operational datasets preferred • Working knowledge of US GAAP, including lease accounting (ASC 842) and fixed assets preferred • Experience in the AI infrastructure, cloud, or data center industry preferred • Must be eligible to work in the United States; Runpod is currently unable to sponsor employment visas

🏖️ Benefits

• Meaningful equity in a fast-growing company; everyone on the team receives stock options • Generous medical, dental & vision plans • Flexible PTO • Remote-first work environment • $1,200 Home Office & Equipment Stipend • Passionate team working on AI infrastructure with learning and ownership opportunities