Finance Subject Matter Expert, AI Models, Evaluations and Data, DeepMind

Google; Mountain View, New York (CA, NY); Presencial; USD 207.000 - 300.000; Jornada completa

Descripción de la vacante

Google DeepMind is seeking a Finance SME to orchestrate AI models, evaluations, and data across Gemini and enterprise agents. You will join a cross-disciplinary team, shaping post-training finance workflows, benchmarks, and deterministic rubrics for multi-step agent reasoning.

You will collaborate with Research Scientists, Post-Training Engineers, and Product Managers to push frontier financial reasoning while ensuring safety and ethics remain a priority.

Formación

• Master's degree in Finance, Economics, quantitative fields, or equivalent practical experience.
• 5 years of institutional finance experience in investigative, modeling-intensive roles (Quantitative Trading, Corporate Finance, or Alternative Asset Management).
• Experience with frontier LLMs, coding agents, or AI evaluation pipelines, including structured prompts and tool-use traces.
• Experience identifying flaws in AI-generated financial models, backtests, or memos, and translating these errors into generalizable grading rules.

Responsabilidades

• Evaluate the AI's step-by-step process across calculations, ledger searches, and code to pinpoint quantitative or accounting errors.
• Create realistic financial tasks (e.g., valuations, backtests, audits) and write golden-standard examples to correct model near-misses.
• Build complex prompts featuring GAAP/non-GAAP differences and conflicting estimates to test AI resilience.
• Create pass/fail checklists for deliverables and draft deceptive, polished-but-wrong answers to stress-test automated graders.
• Teach the AI to efficiently use core financial tools (SQL, etc) and categorize error patterns into reusable templates.

Conocimientos

Frontier LLMs evaluation

Python

SQL

Spreadsheet software

Market data familiarity

Educación

Master's degree in Finance/ Economics/Quantitative fields

CFA/CPA/MBA/JD/MFE/advanced quantitative degree

Herramientas

Python

SQL

Spreadsheet software

Market data feeds tools (EDGAR, Capital IQ, FactSet)

Descripción del empleo

Finance Subject Matter Expert, AI Models, Evaluations and Data, DeepMind

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info_outline

X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.

• Master's degree in Finance, Economics, quantitative fields, or equivalent practical experience.
• 5 years of institutional finance experience in investigative, modeling-intensive roles (Quantitative Trading, Corporate Finance, or Alternative Asset Management).
• Experience with frontier LLMs, coding agents, or AI evaluation pipelines, including structured prompts and tool-use traces.

Experience identifying flaws in AI-generated financial models, backtests, or memos, and translating these errors into generalizable grading rules.

Preferred qualifications:

• CFA, CPA, MBA, JD, Master of Financial Engineering (MFE), or an advanced quantitative degree in Finance, Computer Science, Math, or Economics.
• Background building benchmarks, rubrics, or SFT/RLHF pipelines at AI labs, fintechs, or quantitative teams.
• Domain-specific excellence in Python and SQL (Quant) or advanced, macro-free spreadsheet software and Python/SQL (Alternative Asset Management/Corporate Finance).
• Familiarity with market data feeds, SEC EDGAR, Capital IQ, FactSet, Bloomberg, ERP/EPM, and tax/audit platforms.

About the job

DeepMind is building frontier financial reasoning and agentic capabilities across Gemini and our enterprise agent harnesses. Moving AI from a generalist research assistant to an agent that can autonomously complete financial workflows requiresmore than raw pre-training scale - it requires deep domain mechanics embedded directly into how models are post-trained, how agent harnesses and tools are architected, and how evaluations measure real-world finance.

As a Finance Subject Matter Experts (SME), you will work with models, evaluations, and post-training data in the following three Finance domains -

• Quantitative Trading
• Corporate Finance - specifically with experience across FP&A, Audit and Tax
• Alternative Asset Management

Unlike traditional advisory roles that stop at high-level feedback or static prompt writing, you will sit directly in the model development loop alongside Research Scientists, Post-Training Engineers, and Product Managers. You will prioritize differentiated financial workflows, design end-to-end financial benchmarks, construct atomic and deterministic grading rubrics, diagnose multi-step agent trajectories, repair near-miss model reasoning traces, design verifiable reward signals, and co-build domain-specific agent skills.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

• Evaluate the AI's step-by-step process across calculations, ledger searches, and code to pinpoint quantitative or accounting errors.
• Create realistic financial tasks (e.g., valuations, backtests, audits) and write "gold-standard" examples to correct model near-misses.
• Build complex prompts featuring vague instructions, GAAP/non-GAAP differences, and conflicting estimates to test AI resilience.
• Create pass/fail checklists for deliverables and draft deceptive, polished-but-wrong answers to stress-test automated graders.
• Teach the AI to efficiently use core financial tools (SQL, etc) and categorize error patterns into reusable templates.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.