AI Product Manager - Implementation and Onboarding

About Mentis AI Mentis AI brings together institutional finance expertise and advanced AI research. With offices in London and San Francisco, the team collaborates with top AI labs to improve model reasoning and decision-making for high-stakes financial scenarios. About the AI Residency This part-time residency is designed for experienced research analysts and portfolio managers in investment banking or capital markets. The program focuses on practical applications of advanced AI in real-world financial settings. Key Responsibilities Prompt Engineering: Develop and refine realistic prompts to test the relevance and quality of AI-generated insights. Comparative Analysis: Systematically compare human judgment and AI outputs in M&A, ECM, DCM, and leveraged finance contexts. Framework Development: Translate senior bankers' transaction evaluation and deal structuring methods into challenges that push AI reasoning. Benchmark Construction: Build and validate real-world transaction analyses and valuation frameworks to measure the performance of advanced AI systems. What Makes This Role Distinct See firsthand how AI is changing deal workflows, from pitchbooks to financial modeling and closing transactions. Shape how next-generation AI models approach transaction structuring, valuation, and capital markets execution as an investment banking professional.

About Us Mentis AI operates at the confluence of institutional finance and cutting-edge AI technologies. Our dedicated team merges substantial financial services experience from institutions like Lazard and Partners Group with advanced machine learning and applied AI research. Based in both London and San Francisco, we partner with leading AI research laboratories to enhance model reasoning, generalization, and decision-making in high-stakes financial scenarios.The Opportunity The integration of AI into venture capital workflows is advancing rapidly, from deal sourcing and founder assessment to market evaluation, term sheet negotiation, and portfolio development. This part-time residency offers venture capital professionals the chance to gain practical insights into the construction, evaluation, and enhancement of advanced AI systems within the framework of early and growth-stage investments.Your ResponsibilitiesDevelop Expert Benchmarks: Create and validate real-world investment memoranda, market assessments, and frameworks for evaluating founders that are utilized to assess frontier AI systems.Analyze Model Reasoning: Identify weaknesses in AI-generated venture analyses, pinpointing gaps in logic, assumptions, or investment intuition.Create Evaluation Frameworks: Translate how venture capitalists assess founders, size markets, evaluate competitive landscapes, and build portfolios across various stages and sectors into challenges that test the limits of AI reasoning.Assess Human vs. Machine Judgment: Systematically compare discrepancies between professional venture assessments and AI-generated outputs across deal evaluation, term sheet formulation, and portfolio management environments.Why This Experience MattersBe among the first venture capital professionals to engage directly with how frontier AI models interpret early-stage investing, founder evaluation, and portfolio management.Establish a unique profile for those aiming to merge venture capital with AI, whether in a fund, at an AI startup, or in entrepreneurial ventures.Gain hands-on experience in how AI is transforming venture workflows, from sourcing and due diligence to writing investment memoranda, engaging with boards, and monitoring portfolios.Who You AreA professional with 4+ years of venture capital investing experience at a prestigious VC firm (e.g., Sequoia Capital, Andreessen Horowitz, Accel, Index Ventures).

About Us: At Mentis AI, we stand at the forefront of the intersection between innovative AI systems and institutional finance. Our dedicated team boasts extensive experience from prominent firms such as Lazard and Partners Group, integrating deep financial services expertise with cutting-edge machine learning and AI research. Operating from our key locations in London and San Francisco, we collaborate with leading AI laboratories to enhance the reasoning, generalization, and decision-making capabilities of models in high-stakes financial scenarios.The Opportunity: With the rapid integration of AI into core real estate investment processes—spanning acquisitions, underwriting, asset management, debt structuring, and fund-level reporting—this residency is tailored for institutional real estate private equity (REPE) professionals eager to gain firsthand experience in the development, evaluation, and enhancement of advanced AI systems within the context of REPE investing across various property types and risk profiles.Key Responsibilities:Develop Expert Benchmarks: Construct and validate real-world underwriting models, return analyses, and investment cases to assess frontier AI systems.Stress-Test Model Reasoning: Identify weaknesses in AI-generated real estate analyses, pinpointing logical flaws, erroneous assumptions, or lapses in market intuition.Design Analytical Frameworks: Transform how REPE professionals evaluate acquisitions, structure transactions, and manage assets throughout the investment lifecycle into challenges that stretch AI reasoning capabilities.Assess Human vs. Machine Judgment: Conduct systematic evaluations of the disparities between professional real estate judgment and AI outputs across varying asset classes, risk profiles, and fund structures.Why This Experience Matters:Be among the pioneering real estate investment professionals to engage directly with how frontier AI models assess acquisitions, underwriting, and asset management.Cultivate a unique professional profile positioned at the confluence of real estate and AI—ideal for roles within funds, AI companies, or entrepreneurial ventures.Gain practical insights into how AI is transforming real estate workflows, from deal screening and underwriting to joint venture structuring, asset management, and LP reporting.

About Us Mentis AI operates at the dynamic intersection of institutional investment expertise and cutting-edge AI technologies. Our dedicated team merges extensive asset management experience from industry leaders, including Lazard and Partners Group, with innovative machine learning and applied AI research. With locations in London and San Francisco, we partner with top AI laboratories to enhance model reasoning, generalization, and decision-making in critical financial scenarios.The Opportunity This part-time residency is tailored for senior research analysts and portfolio managers eager to gain valuable insights into the application of AI within the insurance domain. Here, you will experience firsthand the practical use of advanced AI systems.Key Responsibilities:Prompt Development: Create and refine realistic prompts intended for junior roles to assess the relevance and quality of AI-generated insights.Human vs. Machine Evaluation: Systematically analyze discrepancies between professional insurance judgments and AI outputs across investments, underwriting, and actuarial scenarios.Framework Design: Transform the methods used by insurance professionals to assess risk, price policies, manage general account portfolios, and model liabilities into challenges that push the boundaries of AI reasoning.Expert Benchmark Construction: Develop and validate practical underwriting cases, actuarial analyses, and investment frameworks utilized to evaluate leading-edge AI systems.Why This Experience Is ValuableGain hands-on exposure to how AI is revolutionizing insurance operations, from underwriting and pricing to portfolio management and capital modeling.Be at the forefront as one of the first insurance professionals engaged in exploring how frontier AI models analyze carrier operations, risk assessment, and insurance finance.Who You AreA professional with 4+ years of experience at a prominent Property & Casualty or Life insurance carrier.Holding an Associate or VP level position in one of the following functions:Investments: Managing fixed income or multi-asset portfolios within an insurance general account, with knowledge of ALM, duration matching, and regulatory capital constraints (RBC/Solvency II).Underwriting: Engaging in the underwriting process with a strong analytical approach.

About Us Mentis AI operates at the forefront of institutional investment and advanced AI technologies. Our team merges extensive asset management experience from top firms like Lazard and Partners Group with cutting-edge machine learning and AI research. Based in London and San Francisco, we partner with premier AI laboratories to enhance the reasoning, generalization, and decision-making capabilities of models within critical financial environments.The Opportunity This unique residency is tailored for seasoned research analysts and portfolio managers eager to gain invaluable insights and practical experience in integrating AI into their field, utilizing sophisticated AI systems.Your responsibilities will include:Prompt Development: Create and refine realistic prompts that a junior team member would use to assess the relevance and quality of AI-generated insights.Human vs. Machine Evaluation: Methodically examine the differences between professional investment reasoning and AI-generated results across corporate, SME, and retail banking sectors.Framework Design: Transform the methods commercial banks use to engage clients, structure loans, and manage risk into complex challenges that push the boundaries of AI reasoning.Benchmark Construction: Develop and validate practical credit scenarios, client engagement systems, and portfolio management frameworks that assess frontier AI systems.Why This Experience Is InvaluableGain hands-on experience in how AI is transforming workflows in commercial banking, from client onboarding to credit assessment and risk supervision.Join a pioneering group of institutional investment professionals at the cutting edge of AI's impact on borrower assessments, transaction evaluations, and balance sheet risk management across various banking segments.Who You AreA minimum of 4 years of experience with a prominent long-only institutional investment manager (e.g., JPMorgan Chase, Bank of America, Wells Fargo, Citibank, U.S. Bank, Capital One, PNC Bank, Goldman Sachs, Truist Bank, TD Bank)Current role as a Senior Credit/Risk Analyst or Product ManagerExtensive knowledge in corporate, SME, or retail banking, particularly in credit analysis, lending products, and balance sheet/risk management.

About Us Mentis AI operates at the forefront of institutional finance and advanced AI, merging extensive experience in financial services with cutting-edge machine learning and AI research. Our teams, based in San Francisco and London, collaborate with top AI laboratories to enhance decision-making processes in critical financial situations.The Opportunity As AI technology increasingly integrates into essential insurance operations—from portfolio management to underwriting and regulatory assessments—this residency offers insurance professionals a unique chance to gain practical insights into the development, evaluation, and optimization of advanced AI systems within the insurance sector.Your responsibilities will include:Constructing Expert Benchmarks: Develop and validate real-world underwriting scenarios, actuarial evaluations, and investment strategies used for assessing advanced AI systems.Stress-Testing Model Reasoning: Identify and analyze weaknesses in AI-generated insurance evaluations, uncovering flaws in logic, assumptions, or domain understanding.Designing Frameworks: Transform how insurance experts assess risks, set policy prices, manage portfolios, and model liabilities into challenges that extend the boundaries of AI reasoning.Comparing Human vs. Machine Judgment: Rigorously assess the differences between professional insurance decisions and AI outputs in various contexts such as investments and underwriting.Why This Experience Is ValuableBe among the pioneers in the insurance field working directly on how advanced AI models interpret carrier operations and risk management.Enhance your profile if you aim to bridge the gap between insurance and AI, whether at an insurance company, AI firm, or as an entrepreneur.Gain hands-on experience with how AI is transforming insurance processes, from underwriting to pricing and capital modeling.Who You ArePossess 4+ years of experience at a prominent P&C or Life insurance company.Hold an Associate or VP role in areas such as underwriting, actuarial sciences, or portfolio management.

About Us Mentis AI is at the forefront of merging institutional finance with cutting-edge AI technology. Our dedicated team, boasting extensive experience from prestigious firms such as Lazard and Partners Group, collaborates with top-tier AI research laboratories across London and San Francisco. Our mission is to enhance the reasoning, generalization, and decision-making capabilities of models in critical financial scenarios.The Opportunity As AI integrates deeply into core banking functions—from credit underwriting and borrower evaluations to facility structuring and portfolio oversight—this residency offers commercial and corporate banking professionals a unique chance to gain early insights into the development, assessment, and enhancement of advanced AI systems in institutional lending.In this role, you will:Develop Expert Benchmarks: Construct and validate real-world credit analyses, borrower evaluations, and lending frameworks that assess frontier AI systems.Evaluate Model Reasoning: Identify weaknesses in AI-generated credit analyses, pinpointing failures in logic, assumptions, or underwriting intuition.Create Evaluation Frameworks: Transform banker assessments of borrower risk, credit facility structuring, and corporate relationship management into challenges that test AI reasoning capabilities.Analyze Human vs. Machine Judgment: Methodically assess the discrepancies between professional credit evaluations and AI outputs within commercial and corporate lending.Why This Experience Is ValuableBe among the pioneers in banking who directly address how frontier AI models interpret credit underwriting and corporate lending.Cultivate a unique profile at the intersection of banking and AI—ideal for those aspiring to work within financial institutions, AI companies, or entrepreneurial ventures.Gain hands-on experience in how AI is redefining lending processes, from credit approval and borrower assessment to facility structuring and portfolio risk management.Who You Are3–8 years of professional experience in commercial or corporate banking, preferably at a major or regional bank (e.g., J.P. Morgan, Bank of America, Wells Fargo, Citi, PNC, U.S. Bank, Truist, Fifth Third, KeyBank, Huntington).A strong understanding of credit analysis and risk assessment methodologies.Demonstrated interest in AI technologies and their application in financial services.

About Us Mentis AI is pioneering the integration of advanced AI technologies within the realm of institutional finance. Our expert team draws from extensive backgrounds in financial services (including firms like Lazard and Partners Group) and specializes in cutting-edge machine learning and applied AI research. With offices in London and San Francisco, we partner with top AI laboratories to enhance model reasoning, generalization, and decision-making in crucial financial environments.The Opportunity As artificial intelligence transforms core wealth management processes—from portfolio construction to client communications and integrated advisory delivery—this part-time residency invites wealth management and private client specialists to gain invaluable, hands-on exposure to the development, evaluation, and enhancement of sophisticated AI systems tailored for high-net-worth advisory and family office investing.Your Responsibilities:Expert Benchmark Construction: Develop and validate real-world portfolio analyses, financial planning frameworks, and client advisory materials to assess frontier AI systems.Model Reasoning Stress Testing: Identify weaknesses in AI-generated wealth management analyses, pinpointing logical flaws, erroneous assumptions, or shortcomings in advisory intuition.Framework Design: Convert professional practices for building customized portfolios, selecting managers, addressing tax and estate considerations, and communicating investment rationale to sophisticated clientele into challenges that stretch AI reasoning capabilities.Human vs. Machine Judgment Comparison: Evaluate discrepancies between human advisory judgments and AI outputs, particularly in asset allocation, alternative investments, financial planning, and private client scenarios.Why This Experience Matters:You will be among the pioneering wealth management professionals contributing directly to the advancement of AI models relevant to portfolio construction, financial planning, and private client advisory services.This unique opportunity positions you at the intersection of wealth management and AI, valuable for roles in RIAs, private banks, AI firms, or for those aspiring to innovate in the space.Gain practical insights into how AI is transforming advisory workflows, from asset allocation and manager selection to tax-aware investing, estate planning, and client reporting.

About Us Mentis AI operates at the cutting edge of institutional investment and advanced AI systems. Our team merges extensive asset management knowledge from industry leaders with expertise in machine learning and AI research. With offices in London and San Francisco, we partner with top-tier AI laboratories to enhance how models analyze, generalize, and make decisions in critical financial scenarios.The Opportunity This residency program is tailored for seasoned research analysts and portfolio managers seeking invaluable experience in the evolving landscape of AI within wealth management. You'll gain hands-on exposure to cutting-edge AI systems while contributing to significant advancements in the field.Your ResponsibilitiesPrompt Development: Create and refine realistic prompts to assess the relevance and quality of AI-generated insights, simulating junior analyst inquiries.Human vs. AI Evaluation: Methodically compare discrepancies between professional advisory judgments and AI outputs in areas like asset allocation, alternatives, and financial planning.Framework Design: Translate practitioner strategies for portfolio construction, manager selection, and investment communication into challenges that test AI reasoning capabilities.Benchmark Construction: Develop and validate real-world portfolio analyses and advisory materials critical for evaluating frontier AI systems.Benefits of This ExperienceGain practical insights into how AI is revolutionizing advisory workflows, including investment strategies and client reporting.Be among the pioneers in wealth management, directly engaging with how frontier AI models inform portfolio construction and financial planning.Who You AreA professional with over 5 years of experience as a Financial Advisor, Portfolio Manager, or Chief Investment Officer within a Registered Investment Advisor, private banking, or family office environment.Proficient in managing complex client relationships with significant assets under management.

About Us: At Mentis AI, we are pioneering the integration of institutional finance expertise with cutting-edge AI systems. Our dynamic team draws from extensive experience in financial services, including prestigious firms like Lazard and Partners Group, coupled with a strong foundation in machine learning and applied AI research. With operations spanning London and San Francisco, we partner with leading AI laboratories to enhance the reasoning, generalization, and decision-making capabilities of models in high-stakes financial environments.The Opportunity: As AI increasingly transforms the private credit landscape—from initial underwriting and credit approval to facility structuring and ongoing portfolio monitoring—this part-time residency offers direct lending and private credit professionals a unique opportunity to gain early, practical insight into the development, evaluation, and enhancement of advanced AI systems tailored for middle-market lending and credit fund operations.Your Responsibilities:Develop Expert Benchmarks: Construct and validate real-world credit analyses, underwriting scenarios, and portfolio monitoring frameworks to assess frontier AI systems.Stress-Test Model Reasoning: Identify weaknesses in AI-generated credit analyses by diagnosing failures in logic, assumptions, or underwriting intuition.Framework Design: Translate the methods credit professionals use to evaluate borrowers, structure facilities, and monitor middle-market entities into challenges that test the limits of AI reasoning.Assess Human vs. Machine Judgment: Systematically analyze discrepancies between professional credit evaluations and AI outputs across direct lending, unitranche, and structured credit contexts.Why This Experience Matters:You will be among the pioneering private credit professionals to engage directly with how frontier AI models reason about credit underwriting, deal structuring, and portfolio management.This role offers a unique profile for individuals looking to bridge the gap between private credit and AI, whether at a credit fund, an AI company, or through entrepreneurial ventures.Gain hands-on experience with the transformative impact of AI on credit workflows, encompassing underwriting, covenant analysis, loan documentation, portfolio oversight, and amendment processes.

About AfterQuery AfterQuery partners with leading AI labs to advance training data and evaluation frameworks. The team builds high-signal datasets and runs thorough evaluations that go beyond standard benchmarks. As a post-Series A, early-stage company in San Francisco, AfterQuery gives each team member room to shape the future of AI models. Role Overview: Research Scientist - Frontier Data This role focuses on designing datasets and developing evaluation systems that influence how top AI models are trained and assessed. Working closely with research teams at major AI labs, the scientist explores new data collection techniques, investigates where models fall short, and sets up metrics to track progress. The work is hands-on and experimental, moving quickly from hypothesis to live testing and directly impacting large-scale model training. Key Responsibilities Design data slides and analyze data structures to uncover model weaknesses in areas like finance, software development, and enterprise operations. Build and refine evaluation rubrics and reward signals for RLHF and RLVR training approaches. Study annotator behavior and run experiments to improve model capabilities across different domains. Develop quantitative frameworks to measure dataset quality, diversity, and their effect on model alignment and performance. Work with research teams to turn training objectives into concrete data and evaluation needs. What We Look For Experience as an undergraduate or master’s research student (PhD not required). Background or internships with RL environments or AI safety and benchmarking organizations (e.g., METR, Artificial Analysis) is a strong plus. Genuine interest in how data structure, selection, and quality affect model outcomes. Demonstrated skill in designing experiments, acting quickly, and extracting insights from complex data. Comfort working across sectors such as finance, software engineering, and policy. Strong quantitative background and familiarity with LLM training pipelines, RLHF/RLVR methods, or evaluation frameworks. A hands-on mindset focused on building practical solutions.

The Perplexity Research Residency stands as our premier initiative designed to empower outstanding research talent from diverse fields to influence the future of artificial intelligence (AI). This program opens avenues for exceptional researchers, engineers, and analysts from disciplines outside traditional AI research to make significant contributions to the advancement of AI and its implications for users. We welcome applications from theoretical physicists, cognitive scientists, biochemists, quants, mathematicians, philosophers, and distinguished researchers in any other relevant field.For comprehensive details on the Perplexity Research Residency and the application process, please visit our program homepage. We encourage you to review the “What We’re Looking For” section for the specific criteria that will guide our selection of candidates.The annual cash compensation for this position is set at $220,000, prorated for a three-month term.

AI Financial Modeling Extern — F2 AILocation: San Francisco, CA / In-Person or RemoteCommitment: 5+ hours per week | 4 - 12+ weeksCompensation: $50/hrAbout F2 AIAt F2 AI, we are revolutionizing private market investments. Our cutting-edge AI technology streamlines the process of analyzing complex, unstructured deal materials, transforming them into actionable, investment-grade insights in mere minutes. By empowering private credit funds, commercial banks, and private equity firms, we enable faster and more confident capital deployment. Supported by top-tier investors such as NFX and Y Combinator, we are committed to expanding our exceptional product and engineering teams, shaping the future of vertical AI for finance.Role OverviewWe are on the lookout for 1–2 exceptional externs with a strong foundation in Investment Banking or Private Equity to contribute to the development of AI-driven financial modeling on the F2 platform.In this role, you will collaborate closely with our Engineering, Product, and Design (EPD) teams in the San Francisco office to translate institutional-level financial modeling standards into automated, intelligent workflows. This hands-on experience will allow you to shape the future of AI in financial modeling.Key ResponsibilitiesEducate F2 agents on best practices for financial modeling.Create and standardize financial modeling templates optimized for AI execution using a first principles approach.Establish formatting, structure, and best practices that align with institutional modeling standards.Conduct rigorous quality assurance on AI-generated outputs to guarantee precision that meets investor expectations.Test edge cases and assist in identifying potential failures in automated modeling workflows.Ideal Candidate ProfilePossess prior experience in Investment Banking, Private Credit, or Private Equity with extensive exposure to financial modeling.Demonstrated ability to build and audit complex 3-statement, LBO, or credit models from the ground up.Strong understanding of model hygiene, structure, and institutional formatting standards.Critical thinker who enjoys analyzing model logic and stress-testing systems.Passionate about leveraging AI to enhance financial workflows.

At Mentis AI, founded by veterans from Lazard and Partners Group, we are at the forefront of integrating financial expertise with artificial intelligence, with our offices in London and San Francisco. Our mission is to enhance AI model training by bridging the gap between human intelligence and advanced technology.Role Overview: As an Expert AI Trainer in Venture Capital, you will leverage your investment acumen to enhance AI reasoning within venture capital. Your contributions will be pivotal in a structured research initiative, focusing on deal sourcing, evaluating founders, market sizing, term sheet negotiations, and portfolio construction across various stages and sectors.

At Mentis AI, founded by former leaders from Lazard and Partners Group, we operate from our offices in London and San Francisco. Our mission is to integrate profound financial insights into AI model training, effectively bridging the divide between human intelligence and artificial intelligence.Role Overview: In this pivotal role, you will enhance AI-driven decision-making in the venture capital realm by leveraging your investment expertise. Your contributions will be vital in a structured research initiative focused on deal sourcing, founder assessments, market evaluations, term sheet negotiations, and portfolio development across various stages and sectors.

Join Our Innovative Team at David AIDavid AI is pioneering the audio data research landscape. We adopt a rigorous R&D methodology for developing datasets that parallels the standards upheld by leading AI laboratories. Our vision is to seamlessly integrate AI into everyday experiences, with audio serving as the perfect conduit. The evolution of audio AI is rapidly unfolding, yet the availability of high-quality training data remains a critical challenge. This is where David AI steps in.Founded in 2024 by a talented group of former engineers and operators from Scale AI, we have quickly become a trusted partner to numerous FAANG companies and AI research labs. Recently, we secured $50 million in a Series B funding round with notable investors, including Meritech, NVIDIA, and Alt Capital.Our culture is built on sharp intellect, humility, ambition, and a close-knit community. We invite exceptional minds in research, engineering, product development, and operations to join us as we advance the field of audio AI.Research Team OverviewAt David AI, we are convinced that superior model capabilities stem from high-quality, differentiated data. Our research team is dedicated to conducting ambitious, long-term studies into audio technology while collaborating with both internal and external partners to implement cutting-edge research insights into practical applications.Your Role as a Founding Audio AI Research EngineerIn this position, you will establish the research framework that influences how premier AI labs develop their audio models. You will have access to a top-tier team of human AI trainers, robust computing resources, and the autonomy to shape your research agenda.Key ResponsibilitiesCreate and implement comprehensive evaluation frameworks for assessing audio AI capabilities in areas such as speech, emotion detection, conversational dynamics, and acoustic patterns.Investigate and prototype innovative methodologies for audio quality assessment, automated labeling, and optimizing data collection processes.Design focused data collection pipelines aimed at capturing novel, high-value audio capabilities.Develop automated systems for ongoing classifier enhancement and prompt engineering evaluation.Assess cutting-edge models and formulate actionable research strategies.Publish your findings in prestigious conferences.

About Our TeamThe Frontier Systems team at OpenAI is at the forefront of technology, responsible for creating, deploying, and maintaining some of the world's largest supercomputers. These supercomputers are pivotal for training our most advanced AI models, pushing the boundaries of innovation.We transform sophisticated data center designs into operational systems and develop the software infrastructure necessary for extensive frontier model training. Our goal is to ensure these hyperscale supercomputers operate reliably and efficiently, supporting groundbreaking AI research.About the RoleAs a key member of the Frontier Systems team, you will be instrumental in designing the critical infrastructure that ensures our supercomputers function seamlessly for pioneering AI research. In this role, you'll address system-level challenges and implement automation solutions that minimize disruptions during large-scale training processes.Your responsibilities will encompass end-to-end ownership of your projects, allowing you to make significant contributions to our mission. This position is ideal for individuals who excel in diagnosing complex system issues and crafting automation strategies to proactively resolve problems across a vast network of machines.Your Responsibilities Include:Enhancing system health checks to maintain the stability of our hyperscale supercomputers during model training.Conducting in-depth investigations into hardware failures and system-level bugs to uncover root causes.Developing automation tools that monitor and resolve issues across thousands of systems, enabling uninterrupted research progress.You May Be a Great Fit If You Possess:7+ years of hands-on experience in software engineering.Strong proficiency in Python and shell scripting.Expertise in analyzing complex data sets using SQL, PromQL, Pandas, or other relevant tools.Experience in creating reproducible analyses.A solid balance of skills in both building and operationalizing systems.Prior experience with hardware is not a prerequisite for this role.Preferred Qualifications:Familiarity with the intricacies of hardware components, protocols, and Linux tools (e.g., PCIe, Infiniband, networking, power management, kernel performance tuning).Experience with system optimization and performance tuning.

About Distyl AIDistyl AI specializes in creating high-performance AI systems that enhance the fundamental operational processes of Fortune 500 companies. Through a strategic alliance with OpenAI, proprietary software accelerators, and extensive expertise in enterprise AI, we deliver effective AI solutions with swift time-to-value, often within a quarter.Our innovations have empowered Fortune 500 clients in various sectors, including insurance, consumer packaged goods, and non-profit organizations. Joining our team means you will assist organizations in recognizing, developing, and extracting value from their Generative AI investments, frequently for the first time. We prioritize customer needs, working backward from the client's challenges and ensuring we generate financial benefits while enhancing the experiences of end-users.Distyl is guided by seasoned leaders from top-tier companies like Palantir and Apple and enjoys backing from prominent investors including Lightspeed, Khosla, Coatue, Dell Technologies Capital, Nat Friedman (Former CEO of GitHub), Brad Gerstner (Founder and CEO of Altimeter), along with board members from numerous Fortune 500 firms.What We Are Looking ForAt Distyl, we are at the forefront of leveraging AI within enterprises. We seek imaginative researchers who aspire to go beyond incremental enhancements on benchmarks and are eager to redefine the application of software in innovative ways.Our researchers hail from diverse academic disciplines but possess a robust research background, operate in an AI-centric manner, and would find conventional research environments unfulfilling.Key ResponsibilitiesThe AI Systems team is dedicated to architecting complex, comprehensive solutions that integrate perception, reasoning, planning, and execution. Researchers amalgamate various components (LLMs, retrievers, evaluators, memory systems, and execution agents) into resilient, scalable systems that deliver consistent performance across dynamic enterprise workflows.Researchers in AI Systems examine the principles governing intricate system interactions. They analyze coordination, information flow, and emergent behavior across multiple agents and models. Their research reveals the foundational mechanics of robustness, composability, and alignment, ultimately establishing the design paradigm for constructing intelligent systems.

Join Our Innovative TeamAt OpenAI, our Safety Systems team is at the forefront of ensuring that AI models are safe, robust, and reliable for real-world applications. We are committed to the principle set forth in our charter: to widely distribute the benefits of AI technology. Our Health AI unit is dedicated to providing equitable access to high-quality medical information. By bridging AI safety research with healthcare applications, we strive to develop trustworthy AI systems that empower medical professionals and enhance patient care.The OpportunityWe are on the lookout for passionate researchers who are eager to contribute to AI safety and improve health outcomes globally. As a Health AI Research Scientist, your role will involve developing safe and effective AI models tailored for healthcare applications. You will implement innovative methods to enhance the behavior, knowledge, and reasoning capabilities of our models. This necessitates research into safety and alignment techniques that can be generalized to ensure a beneficial AGI.This position is based in San Francisco, CA, utilizing a hybrid work model (3 days in the office per week) and we provide relocation assistance for new hires.Key Responsibilities:Design and implement scalable methods to enhance the safety and reliability of our models, such as Reinforcement Learning from Human Feedback (RLHF), automated red teaming, and scalable oversight.Assess methodologies using health-related data to ensure models deliver accurate, reliable, and trustworthy information.Develop reusable libraries to apply general alignment techniques across our models.Proactively analyze the safety of our models and systems, identifying potential risk areas.Collaborate with cross-functional teams to embed safety methods into core model training and drive safety improvements in OpenAI products.Ideal Candidate Profile:Align with OpenAI’s mission to ensure AGI benefits everyone and resonate with our charter.Exhibit a strong passion for AI safety and enhancing global health outcomes.Possess 4+ years of experience in AI research, with a focus on health applications.Demonstrate proficiency in machine learning frameworks and safety techniques.Showcase effective communication skills for cross-team collaboration.