Strategic Finance Lead - Compute
Perplexity is hiring a Strategic Finance Lead - Compute for a remote role open to applicants in United States. It pays $190k-$240k a year and Level rates it ; you can apply on Perplexity.
Level's read on this job
- Works on AI ●●●○ is how Level rates this finance role: the daily work is on AI products, without building the model.
- Pay on this posting starts 77% higher than the typical finance posting on Level.
- This is listed as a remote role.
- The posting mentions financial modeling, gpu compute and capacity planning among its tools and skills.
- Perplexity has 130 other open roles on Level.
AI in this role
Strategic Finance Lead managing GPU compute fleet economics, capacity forecasting, and infrastructure investment decisions.
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
How we rate this
Strategic Finance Lead - Compute at Perplexity rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $190k
- Typical finance job
- $107k
This posting starts 77% above the typical finance job. See finance jobs
Questions you could be asked
- Tell me about a project where financial modeling was part of your work. What did you do?
- Tell me about a project where gpu compute was part of your work. What did you do?
- Tell me about a project where capacity planning was part of your work. What did you do?
- Tell me about a project where cost analysis was part of your work. What did you do?
- Tell me about a project where roi analysis was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Financial Modeling, GPU Compute, Capacity Planning, Cost Analysis, and Roi Analysis. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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