Compute Analyst

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Responsibilities

• At Applied Compute, compute is our core input that makes our post-training and agent infrastructure possible. As Compute Analyst, you'll run the analyses behind how we source, price, and use the GPU capacity that powers everything we train, serve, and deploy for our customers. You'll work closely with the finance and research teams to turn a fragmented, fast-moving supply market into clear numbers the company can make big decisions on. This role suits someone who wants to learn the economics of AI infrastructure from the inside, with real ownership from day one.
• Build and own the models behind our compute unit economics, including effective $/GPU-hour, cost per training run, cost per token served, utilization, and goodput
• Track the global GPU market: pricing, availability, and terms across hyperscalers, neoclouds, regional operators, and emerging providers, plus outline the tradeoffs between hardware generations
• Support live negotiations with quote benchmarking, scenario analysis, side-by-side comparisons of term sheets and contract structures, and deal memos that make the recommendation clear
• Work with research and engineering to turn training roadmaps, RL workloads, and inference growth into concrete capacity forecasts
• Monitor our fleet: commitments, reservation coverage, idle capacity, and utilization by workload, helping surface problems before they become costly
• Partner with finance on compute budgeting, commitment tracking, and margin analysis across our training and inference products
• Build TCO models that combine pricing, reliability, acceptance-testing results, and goodput data to inform sourcing decisions
• Automate the reporting and dashboards that give leadership a real-time view of our compute position

Requirements

• 2–5 years in a highly analytical role, such as investment banking, private equity, consulting, strategic finance or FP&A, or cloud/infrastructure analytics
• Excellent financial modeling skills and native fluency in unit economics, margin structure, and scenario analysis
• Strong technical skills: comfortable in SQL and Python, and happy to pull and clean your own data
• Real curiosity about the AI compute market: providers, accelerators, pricing dynamics, and where things are heading
• Clear communication, with the ability to explain complex analysis simply to finance, engineering, and leadership
• High ownership, with a habit of seeing gaps and building the fix before anyone asks

Strong candidates also have

• Experience in cloud cost management / FinOps, data centers, energy, or other capacity-constrained infrastructure markets
• Familiarity with GPU performance concepts (MFU, interconnect, cluster reliability) and how they affect effective cost
• Exposure to reserved-capacity, take-or-pay, or other long-term commercial contract structures
• An AI-native way of working, using LLMs, automation, and programmatic tools to move faster

Benefits

• The U.S. base salary range for this full-time position is $226,000–$325,000. Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a comprehensive benefits package designed to support you both personally and professionally. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
• This role is based in San Francisco. We work from our office in the Mission. We offer:
• 100% employer-paid health insurance coverage for you and your family
• Unlimited PTO
• Daily lunches and dinners
• Transportation and relocation support
• 5% 401(k) match