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Perplexity
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Strategic Finance Lead - Compute

PerplexitySan Francisco
RemoteFinancesenior$190,000 - $240,000
Source checked 4 hours ago. · Posted 29 days ago.
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Role details

ABOUT THE ROLE

  • We are seeking a Strategic Finance Lead for our GPU compute fleet. In this role, you will be a key partner to our inference and infrastructure teams, providing financial expertise to optimize our compute investments and drive capacity decisions.
  • In this role, you'll develop deep expertise in the economics of AI compute, from token-level serving cost to the long-range financial planning of our GPU fleet.
  • You'll build the models that inform Perplexity's capacity and make-versus-buy decisions, own the internal-cost analysis that underpins internal and external token pricing, and translate complex infrastructure dynamics into clear financial narratives for leadership.
  • This is a high-impact role for someone who thrives at the intersection of finance and infrastructure, and who is energized by building frameworks from scratch in a fast-moving environment.
  • This position is based in San Francisco and requires in-person attendance 2-3 days per week.

KEY RESPONSIBILITIES

  • Finance lead for GPU compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance
  • Build and maintain detailed bottoms-up financial models for the GPU fleet, including capacity forecasts, cost driver analyses, and investment scenario modeling
  • Develop deep expertise in GPU vendor contracts, pricing structures, and cost drivers, and surface optimization opportunities across the fleet
  • Serve as subject matter expert for Perplexity's compute capacity plan, owning source of truth on utilization, committed-versus-consumed spend, and capacity by vendor and cluster
  • Build internal token-cost curves distinguishing marginal from fully loaded serving cost, and translate them into internal and external token pricing
  • Analyze the ROI of in-house inference and training, including opportunity cost across chip types, cluster configurations, and workloads, distilled into a framework for capacity deployment
  • Partner closely with inference and infrastructure engineering to understand how serving and training workloads scale, and translate those technical dynamics into financial frameworks

YOU MAY BE A GOOD FIT IF YOU HAVE

  • Exceptional analytical skills with an ability to synthesize data into compelling insights and develop complex financial operating models
  • Extraordinary problem-solving and critical thinking abilities to develop new frameworks for assessing utilization and capital efficiency in a rapidly evolving industry
  • Attention to detail and patience for getting to the source of truth on complex and interconnected contract and usage data
  • Comfort being the finance person in the room with engineering leads and vendor counterparts, and adept at communicating complex financial information to non-finance audiences
  • A proven track record of partnering with technical teams to drive financial optimization initiatives, building enough trust to become indispensable to their roadmap and resourcing decisions
  • A bias toward action, strong work ethic, and experience driving operational outcomes under tight timelines
  • Background in AI, ML, or high-performance, large-scale computing infrastructure, including data centers and cloud service providers

PREFERRED QUALIFICATIONS

  • 4+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking, preferably with infrastructure or datacenter experience
  • Experience in cloud or GPU infrastructure financial management, including direct work with major cloud service providers or neoclouds
  • Direct experience with committed-use economics — reserved capacity, savings plans, committed-use discounts — and GPU procurement
  • Deep expertise in GPU vendor economics, contract structures, and pricing models
  • Experience with chip architecture economics and optimization strategies
  • Proficiency with financial modeling tools