Finance & Strategy, Compute Infrastructure
San Francisco, CA | New York City, NYFull-TimeMid-levelAccounts / Finance
About Anthropic
- Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
- We are seeking a Strategic Finance Lead to provide finance leadership for our accelerator investments. In this role, you will be a key partner to our compute teams, providing financial expertise and guidance to optimize our compute investments and drive strategic decision-making
- In this role, you’ll develop deep expertise in the economics of AI compute, from the unit economics of individual training runs to the long-range financial planning of our accelerator fleet. You’ll build financial models that inform Anthropic’s investment decisions, own planning and forecasting processes for major cost centers, and translate complex technical dynamics into clear financial narratives for leadership.
- This is a high-impact role for someone who thrives at the intersection of finance and technology, and who is energized by building frameworks from scratch in a fast-moving environment.
Accelerator Compute Finance
- Finance lead for accelerator compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance
- Build and maintain detailed bottoms-up financial models for accelerator infrastructure, including long-range forecasts, cost driver analyses, and investment scenario modeling
- Develop deep expertise in accelerator compute contracts, pricing structures, and cost drivers, and surface optimization opportunities across our infrastructure
- Support the implementation and management of financial planning tools (e.g., Pigment), ensuring our models and processes scale with the organization
- Finance lead for accelerator compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance
- Build and maintain detailed bottoms-up financial models for accelerator infrastructure, including long-range forecasts, cost driver analyses, and investment scenario modeling
- Develop deep expertise in accelerator compute contracts, pricing structures, and cost drivers, and surface optimization opportunities across our infrastructure
- Support the implementation and management of financial planning tools (e.g., Pigment), ensuring our models and processes scale with the organization
Model R&D Finance
- Analyze the economics of model training and research compute, including ROI across different dimensions like training run sizes, chip types, data, etc, and track how these economics evolve over time
- Partner closely with engineering and research teams to understand how training and reinforcement learning processes scale, and translate those technical dynamics into financial frameworks
- Serve as the finance lead for all data partnerships and human data operations, including budgeting, forecasting, unit economics, and analysis
- Analyze the economics of model training and research compute, including ROI across different dimensions like training run sizes, chip types, data, etc, and track how these economics evolve over time
- Partner closely with engineering and research teams to understand how training and reinforcement learning processes scale, and translate those technical dynamics into financial frameworks
- Serve as the finance lead for all data partnerships and human data operations, including budgeting, forecasting, unit economics, and analysis
You may be a good fit if you have
- 7+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking, preferably with infrastructure, datacenter, or technology infrastructure experience
- 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 navigate complex financial challenges
- Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences
- Proven track record of partnering with technical teams to drive financial optimization initiatives
- Excitement about working in a fast-paced, dynamic environment and adapt well to change
- Possess a bias towards action, strong work ethic, and have experience driving operational outcomes under tight timelines
- Strong relationship building, business judgment, process management, and communication skills
- Are passionate about Anthropic's mission to build safe, transformative AI systems
- Background in AI, ML, or high-performance, large-scale computing infrastructure, including data centers, cloud service providers, etc
- 7+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking, preferably with infrastructure, datacenter, or technology infrastructure experience
- 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 navigate complex financial challenges
- Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences
- Proven track record of partnering with technical teams to drive financial optimization initiatives
- Excitement about working in a fast-paced, dynamic environment and adapt well to change
- Possess a bias towards action, strong work ethic, and have experience driving operational outcomes under tight timelines
- Strong relationship building, business judgment, process management, and communication skills
- Are passionate about Anthropic's mission to build safe, transformative AI systems
- Background in AI, ML, or high-performance, large-scale computing infrastructure, including data centers, cloud service providers, etc
Strong candidates may also have
- 3+ years of experience specifically in cloud infrastructure financial management
- Experience working directly with major cloud service providers (AWS, GCP, Azure)
- MBA or other advanced degree in finance, economics, or business
- Deep expertise in cloud service provider economics, contract structures, and pricing models
- Experience with chip architecture economics and optimization strategies
- Proficiency with financial modeling tools and languages (SQL, Python, Excel)
- 3+ years of experience specifically in cloud infrastructure financial management
- Experience working directly with major cloud service providers (AWS, GCP, Azure)
- MBA or other advanced degree in finance, economics, or business
- Deep expertise in cloud service provider economics, contract structures, and pricing models
- Experience with chip architecture economics and optimization strategies
- Proficiency with financial modeling tools and languages (SQL, Python, Excel)
- The annual compensation range for this role is listed below.
- For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
How we're different
- We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
- The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
