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San Francisco, California, United States
Hybrid
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.
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
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
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
