About Us Mentis AI works at the intersection of institutional finance expertise and frontier AI systems. Our team combines deep financial services experience (Lazard, Partners Group) with machine learning and applied AI research. Operating across London and San Francisco, we collaborate with leading AI labs to improve how models reason, generalize, and make decisions in high-stakes financial contexts. The Opportunity 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 system. You will: - Prompt: Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. - Compare human vs. machine judgment: Systematically evaluate divergence between professional banking judgment and AI outputs across M&A, ECM, DCM, and leveraged finance contexts. - Design frameworks: Translate how senior bankers evaluate transactions, structure deals, and advise clients through origination, execution, and close into problems that push the limits of AI reasoning. - Construct expert benchmarks: Build and validate real-world transaction analyses, valuation frameworks, and deal materials used to evaluate frontier AI systems Why This Experience Is Valuable - Hands-on exposure to how AI is reshaping deal workflows, from pitching and origination through financial modeling, fairness opinions, and transaction close. - You will be among the first investment banking professionals to work directly on how frontier AI models reason about transaction structuring, valuation, and capital markets execution. Who You Are - 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 - Ability to articulate investment banking judgment clearly and precisely in writing - Genuine intellectual curiosity about the application of AI in financial services Residency Structure - Commitment: 15+ hours/week, flexible scheduling - Location: Remote globally, or in-person if based in London - Compensation: Hourly rate depending on experience - Start date: Immediate / Rolling

About Us Mentis AI works at the intersection of institutional finance expertise and frontier AI systems. Our team combines deep financial services experience (Lazard, Partners Group) with machine learning and applied AI research. Operating across London and San Francisco, we collaborate with leading AI labs to improve how models reason, generalize, and make decisions in high-stakes financial contexts. The Opportunity 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 system. You will: - Prompt: Develop and iterate realistic prompts that you would ask a junior role to test the relevance and quality of AI-generated insights. - Compare human vs. machine judgment: Systematically evaluate divergence between professional banking judgment and AI outputs across M&A, ECM, DCM, and leveraged finance contexts. - Design frameworks: Translate how senior bankers evaluate transactions, structure deals, and advise clients through origination, execution, and close into problems that push the limits of AI reasoning. - Construct expert benchmarks: Build and validate real-world transaction analyses, valuation frameworks, and deal materials used to evaluate frontier AI systems Why This Experience Is Valuable - Hands-on exposure to how AI is reshaping deal workflows, from pitching and origination through financial modeling, fairness opinions, and transaction close. - You will be among the first investment banking professionals to work directly on how frontier AI models reason about transaction structuring, valuation, and capital markets execution. Who You Are - 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 - Ability to articulate investment banking judgment clearly and precisely in writing - Genuine intellectual curiosity about the application of AI in financial services Residency Structure - Commitment: 15+ hours/week, flexible scheduling - Location: Remote globally - Compensation: Hourly rate depending on experience - Start date: Immediate / Rolling

Role Description - Author original computer science questions that test deep conceptual understanding, not surface-level recall. - Ensure questions are unambiguous, self-contained, and precisely defined with all necessary information in the problem statement. - Rate each question's difficulty: Medium (intro undergraduate), Hard (advanced undergraduate), or Expert (post-graduate and above). - Provide 1 correct answer and 9 plausible but subtly incorrect alternatives that challenge expert-level solvers. - Write step-by-step Chain-of-Thought solutions with clear, concise intermediate steps in markdown format. - Supply 1–5 academic references per question from reputable sources like peer-reviewed journals or university repositories. - For verification tasks: flag issues with clarity, completeness, precision, or solvability and justify any edits made. Qualifications - Must-Have: PhD or doctoral candidate in Computer Science, Electrical Engineering, or a closely related field. - Master's degree considered for candidates with exceptional depth in a specific subdomain. - Strong command of graduate-level CS theory, algorithms, systems design, and/or machine learning. - Excellent written English and ability to express complex ideas clearly and concisely. - Preferred: Research publications, industry experience at top tech companies, or competitive programming background. Requirements - Contract position. - Compensation: $35–$75/hour. - Location: Remote. - Commitment: 10+ hours/week. Company Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Title: Research Scientist, Conversational AI Location: New York / Mountain View Type: Full-time Workplace: hybrid Category: Research Job Description: At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. We work in tight, skilled teams, prioritize clarity over complexity, and continuously evolve through curiosity, data, and craftsmanship. We’re seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it’s Day 1. We're a globally diverse team with hubs in New York City, Mountain View, Latin America, and India—embracing both hybrid and remote work to bring the best minds together, wherever they are. If you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we’d love to talk. This is more than a job—it’s a journey. Position Overview: We are expanding our research team and looking for an experienced Research Scientist specializing in Conversational AI & Machine Learning. In this role, you will work on solving scientific challenges related to Conversational AI to build domain-specific, real-world solutions. You will have the opportunity to leverage the massive amounts of data generated by our products to ask fundamental research questions, while deploying AI features into real-world applications. What you'll do - Hands-on Research: Be deeply involved in hands-on technical work in any and all aspects of research projects from early exploration to working prototypes to achieve successful real-world applications. - Research Leadership: Identify promising applications of AI relevant to ASAPP’s core mission, formulate and advocate for research programs in those areas, and take ownership of driving impactful research initiatives. - Collaboration & Advocacy: Work with cross-functional teams to socialize your research findings, advocate for their application, and guide the productization of those findings to improve customer experience solutions. - Documentation & Publication: Document significant experimental results, contribute to publishing peer-reviewed papers, and participate in patenting innovations. - Mentorship: Mentor and guide junior researchers, helping them develop their skills in independent research and the communication of their findings. What we're looking for - Education: PhD in a relevant field (such as Computer Science, Electrical Engineering, Linguistics, etc.) - Technical Expertise: Strong research experience in LLMs, Conversational AI, or Speech systems, including practical knowledge of algorithm design, model development, and experimental evaluation. Ideally with a focus on real-world applications. - Mentorship: Experience in coaching and guiding junior researchers or research engineers. - Hands-on Contribution: As an individual contributor, you’ll be expected to lead experiments, perform hands-on research, and drive the execution of innovative projects. - Enthusiasm: A passion for continued learning and deepening expertise in machine learning and AI, with a strong desire to apply research in impactful ways. What we'd like to see - Experience with Spoken Conversational AI applications or Speech LLMs. - Ability to develop and lead independent research programs. - A collaborative mindset, eager to share research findings and drive their application across product teams. - Experience in a startup environment, with the ability to balance deep research and rapid execution. $190,000 - $230,000 a year Compensation package also includes an annual performance bonus on top of the listed salary range Separately, we also offer a compelling equity grant comprised of stock options Benefits include: Competitive compensation with stock options Comprehensive medical, vision, and dental insurance 401k matching Fitness and wellness stipend Mental well-being benefits Professional learning and development stipend Parental leave, including adoptive and foster parents 3 weeks paid time off (increases with tenure) along with sick leave, bereavement and jury duty ASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at careers@asapp.com to obtain assistance. #LI-AG1 #LI-Hybrid We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.