Mentis AI

• Case Review & Coding: Review individual coding cases (estimated 30–45 minutes per case), applying accurate medical codes in line with project guidelines and standards. • Quality Assurance & Data Accuracy: Ensure consistent and accurate application of medical codes following provided guidelines and project standards. • Platform-Based Review: Use a dedicated labeling platform to review, code, and validate cases efficiently. • Feedback & Collaboration: Provide feedback to improve coding guidelines, identify ambiguities in source data, and support the improvement of AI-assisted coding mappings.

• Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. • Systematically evaluate divergence between professional venture judgment and AI outputs across deal evaluation, term sheet structuring, and portfolio management contexts. • Translate how VCs evaluate founders, size markets, assess competitive dynamics, and construct portfolios across stages and sectors into problems that push the limits of AI reasoning. • Build and validate real-world investment memos, market analyses, and founder evaluation frameworks used to evaluate frontier AI systems.

• Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. • Systematically evaluate divergence between professional advisory judgment and AI outputs across asset allocation, alternatives, financial planning, and private client contexts. • Translate how practitioners build tailored portfolios, select managers, navigate tax and estate considerations, and communicate investment rationale to sophisticated clients into problems that push the limits of AI reasoning. • Build and validate real-world portfolio analyses, financial planning frameworks, and client advisory materials used to evaluate frontier AI systems.

• Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. • Systematically evaluate divergence between professional insurance judgment and AI outputs across investments, underwriting, and actuarial contexts. • Translate how insurance professionals evaluate risk, price policies, manage general account portfolios, and model liabilities into problems that push the limits of AI reasoning. • Build and validate real-world underwriting cases, actuarial analyses and investment frameworks used to evaluate frontier AI systems.

• Help improve AI reasoning across investment banking and capital markets by contributing your deal experience to a structured research project. • Evaluating, generating, and refining content that reflects how senior IB professionals think through transactions from origination and pitching through execution and close.

Our founders are ex-Lazard and Partners Group, and we're headquartered in London and San Francisco. Mentis AI brings real-world expertise from finance into AI model training. We bridge the gap between human and artificial intelligence. About this role: You will contribute direct lending and private credit expertise to an AI training project, helping develop training data that reflects how credit professionals underwrite deals, structure facilities, and monitor middle-market borrowers across the private credit spectrum. What we're looking for: - 3–8 years of private credit or direct lending experience at a BDC, direct lending platform, or credit fund (e.g., Ares Capital, Golub Capital, HPS Investment Partners, Blue Owl Capital, Apollo, Oaktree) - Associate, VP, or Director level - Strong credit underwriting skills: financial modeling, covenant analysis, collateral assessment, and credit memo writing - Experience structuring first lien, unitranche, second lien, or mezzanine facilities for sponsor-backed or non-sponsored borrowers - Familiarity with loan documentation, portfolio monitoring, and amendment/waiver processes Project Info (Requirements): - Minimum 15 hours commitment per week - Remote asynchronous contract - Join a research project with an elite AI lab. Help improve AI decision-making in private credit underwriting, deal structuring, and portfolio management

Our founders are ex-Lazard and Partners Group, and we're headquartered in London and San Francisco. Mentis AI brings real-world expertise from finance into AI model training. We bridge the gap between human and artificial intelligence. About this role: You will help improve AI reasoning across investment banking and capital markets by contributing your deal experience to a structured research project. The work involves evaluating, generating, and refining content that reflects how senior IB professionals think through transactions from origination and pitching through execution and close. What we're looking for: - 3–7 years of experience in investment banking or capital markets at a bulge bracket or elite boutique (e.g. Goldman Sachs, Morgan Stanley, J.P. Morgan, Bank of America, Citi, Barclays, UBS, Deutsche Bank, Wells Fargo, Evercore, Moelis, Centerview, Lazard, Jefferies) - Associate, VP, or Director level across M&A, industry coverage, ECM/DCM, leveraged finance, or syndicate - Deep expertise in at least one of: M&A deal structuring and valuation, equity or debt capital markets execution, sector-specific coverage, or syndicate/book-running - Strong financial modeling skills (including LBO, 3-statement, DCF) and comfort with complex transaction analysis, fairness opinions, and client-facing materials Residency Structure - Commitment: 15+ hours/week, flexible scheduling - Location: Remote globally, or in-person if based in London or San Francisco - Compensation: Paid professional engagement - Start date: Immediate / Rolling

Our founders are ex-Lazard and Partners Group, and we're headquartered in London and San Francisco. Mentis AI brings real-world expertise from finance into AI model training. We bridge the gap between human and artificial intelligence. About this role: You will bring institutional real estate investment expertise to an AI training project covering acquisitions, underwriting, asset management, and fund-level analytics capturing how top REPE professionals evaluate opportunities, structure transactions, and manage assets across property types. What we're looking for: - 3–8 years of experience in institutional real estate private equity (e.g., Blackstone Real Estate, Brookfield Asset Management, Starwood Capital, Lone Star Funds) - Associate or VP level in acquisitions or asset management - Strong real estate financial modeling: DCF, waterfall structures, development proformas, and return attribution - Experience across multiple asset classes (multifamily, office, industrial, hospitality, retail) and risk profiles (core, value-add, opportunistic) - Familiarity with debt structuring, joint venture documentation, and LP reporting Project Info (Requirements): - Minimum 15 hours commitment per week - Remote asynchronous contract - Join a research project with an elite AI lab. Help improve AI decision-making in real estate acquisitions, underwriting, and asset management

• Help improve AI reasoning across the insurance industry • Contribute expertise to a structured training project

Role Description This residency is designed for senior research analysts and portfolio managers who want exposure and a meaningful experience towards the direction of AI in your domain and earn early, practical exposure at using advanced AI systems. - Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. - Systematically evaluate divergence between professional investment reasoning and AI outputs across equities, fixed income, and multi-asset contexts. - Translate how institutional investors evaluate securities, construct portfolios, and manage risk into problems that push the limits of AI reasoning. - Build and validate real-world investment cases, securities analyses, and portfolio management frameworks used to evaluate frontier AI systems. Hands-on exposure to how AI is reshaping investment workflows, from fundamental research and portfolio construction to client communication and risk attribution. You will be among the first institutional investment professionals to work directly on how frontier AI models reason about public markets and portfolio management. Qualifications - 4+ years of experience at a major long-only institutional manager (e.g. BlackRock, Vanguard, Fidelity, Capital Group, T. Rowe Price, Wellington, PIMCO, MFS, Neuberger Berman, Jennison, Artisan Partners). - Senior Research Analyst or Portfolio Manager level. - Deep expertise in equities, fixed income, or multi-asset portfolio management. - Experience conducting fundamental analysis, writing investment commentary, and engaging with company management or issuers. - Familiarity with client reporting, risk attribution, and investment policy constraints. - Genuine intellectual curiosity about the application of AI in institutional finance. Requirements - Commitment: 15+ hours/week, flexible scheduling. - Location: Remote globally. - Compensation: Hourly rate depending on experience. - Start date: Immediate / Rolling.