Compute Analyst

Job description

# **The role** 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. **What you'll do** - 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 **What we're looking for** - 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 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. # **About us** Applied Compute builds Specific Intelligence for the enterprise. We provide the continual learning infrastructure for companies to build agent workforces trained on proprietary data and institutional expertise. Our researchers and platform embed directly within customer environments to build custom evals, train models, and deploy agents that get better with use. - **Why we’re excited:** We get to work at a rare intersection. Our product team builds the platform powering a new generation of digital coworkers. Our research team pushes the frontier of post-training and reinforcement learning. Our applied AI team sits side-by-side with customers as they ship agents into production. This combination of strong product, deep research, and boots on the ground is what we believe it takes to bring AI to the enterprise. We are product-led, research-enabled, and forward-deployed. - **Who we are**: We’re a team of engineers, researchers, and operators. Many of us are former founders. We've built RL infrastructure at OpenAI, data foundations at Scale AI, and systems at Together, Two Sigma, Watershed, and others. We work with F50 customers and are fortunate to be backed by partners like Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks. - **Who Thrives Here**: We're looking for people who are excited about applying novel research and complex systems to real-world problems. Our team genuinely enjoys working with customers: listening, empathizing, and understanding how work actually gets done in their organizations. Former founders, people who've built a lot of side projects, or anyone who's shown they can own something end-to-end, tend to do well here. # **Benefits & Logistics** This role is based in San Francisco. We work from our office in the Mission. We offer: - Competitive compensation and equity - 100% employer-paid health insurance coverage for you and your family - Unlimited PTO - Paid parental leave - Daily lunches and dinners - Transportation and relocation support - 5% 401k match We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the process with you. We encourage you to apply even if you do not believe you meet every single qualification. As set forth in Applied Compute’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.