About the Role
- This is a critical strategic role situated at the intersection of infrastructure, finance, and AI strategy within Google DeepMind’s Technology Strategy function. You will join the Technical Intelligence (TI) team with a dual mission: to analyse the "supply side" of the AI revolution (infrastructure and cloud economics) and to provide decisive competitive advantages by monitoring the external Large Model (LM) landscape. Your insights will directly inform Google’s strategic planning, investment decisions, and technical roadmaps, ensuring we anticipate market moves rather than react to them.
- Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority. You will serve as a vital intelligence node for the external AI ecosystem, acting as the expert on both the AI infrastructure market and competitor activity. You will analyse how compute power is being financed, built, and priced, while simultaneously synthesising public planning records and industry reports to track the strategies of key industry players. You will partner closely with Google Cloud (IaaS and Vertex), the Gemini App team, Gemini Research, Google Infrastructure, and Corporate Finance.
Responsibilities
- Market Strategy & Ecosystem Analysis: Deeply analyse the strategies and roadmaps of key industry players, including major AI labs, Hyperscalers, and specialised NeoClouds. Identify forthcoming technical releases, strategic partnerships, and shifts in model architecture.
- Infrastructure & Resource Intelligence: Track external resource commitments, including data center footprint expansions, compute cluster acquisitions, and supply chain bottlenecks (e.g., gigawatt-scale projects, chip supply). Estimate future training capabilities across the industry.
- Financial Modeling & Economics: Build financial models for AI competitor pricing structures, burn rates, and unit economics for AI workloads. Analyse financing strategies for GPU/TPU acquisition and assess the sustainability of competitor strategies.
- Strategic Reporting: Develop detailed quarterly reports and ad-hoc memos on the state of the global AI compute market and competitive landscape. Translate complex technical, business, and supply chain signals into clear narratives for executive leadership.
- Investment & Partnership Support: Provide data-driven diligence and recommendations to support decisions regarding M&A targets, external compute partnerships, and strategic infrastructure investments.
Requirements
- Bachelor's degree in a quantitative or technical field (e.g., Finance, Economics, Engineering, Computer Science, Physics) or equivalent practical experience.
- 3+ years of experience in technical / go-to-market product management, equity research, strategic consulting, or competitive intelligence within the technology sector.
- Experience in financial modeling and analysis, with the ability to estimate costs and unit economics of technical projects.
- Demonstrated ability to synthesise disparate data sources (technical papers, financial reports, news and proprietary data sources) into coherent strategic insights.
- Strong understanding of the Generative AI landscape, including familiarity with Large Language Models (LLMs) and the key industry players.
Qualifications
- CFA, or Master's degree in a relevant field.
- Solid understanding of the AI hardware ecosystem (GPUs, TPUs, ASICs, data centers) and / or the Generative AI landscape (LLMs, key players).
- Direct experience working for a major AI Cloud provider or for an AI lab in a hardware strategy role on: AI cloud economics, AI infrastructure strategy, investment banking covering hardware/semiconductors, or technical product management in AI cloud computing.
- Direct experience working for an AI lab in a go-to-market role with solid understanding of competitive positioning, market trends and pricing considerations.
- Familiarity with the semiconductor supply chain (major chip designers and foundries) and its impact on cloud capacity.
- Excellent written and verbal communication skills, with experience presenting high-stakes analysis to senior executives.