--- title: 'Member of Technical Staff | Quantitative Development at Poesis' canonical: 'https://feeny.ai/job/member-of-technical-staff-quantitative-development-poesis-san-francisco-dd8y7arw60qp' type: 'job' last_seen: '2026-09-09' --- # Member of Technical Staff | Quantitative Development at Poesis - **Company:** Poesis - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-06-11 - **Last confirmed live:** 2026-09-09 - **Apply:** https://jobs.ashbyhq.com/poesis/95065a70-aa63-4469-b98c-087201a28d77 ## Job description ## ABOUT POESIS Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal. ## ABOUT THE ROLE We’re hiring a Quantitative Developer to help turn research ideas into production-grade code. You’ll help build data pipelines, implement models and ensure results are clean, reproducible and explainable. You’ll work alongside Poesis’ Chief Scientist, CEO and engineering leadership to turn large-scale data and quantitative research into models, signals and tools that drive investment decision-making. ## RESPONSIBILITIES - Rapidly implement and iterate on research ideas and model prototypes. - Clean, process, and join financial and fundamental datasets from professional and public sources. - Build and maintain processes for feature generation, back-testing, and model evaluation. - Run experiments, summarize results, and report findings to leadership. - Contribute to code quality: testing, documentation, and integration into shared systems. - Support the team in defining data schemas, APIs, and reproducibility standards. - Implement, test, and refine models, signals, and analytical workflows. - Maintain a consistent cadence of deliverables, focusing on iteration speed and reliability. ## REQUIRED COMPETENCIES - 3+ years of professional experience building the model infrastructure, data pipelines, and analytical tools to drive trading strategies - Strong Python skills (pandas, numpy, scipy, matplotlib); comfort with SQL. - Skill working with Claude Code, Codex, or other coding agents. - Proficiency working with real-world financial datasets and building reproducible analyses or pipelines. - Understanding of statistics, regression, optimization, and ML fundamentals. - Clear communicator who can explain technical findings to non-specialists. - BS/MS/PhD in Computer Science, Mathematics, Statistics, Physics, Finance or related quantitative field. ## PREFERRED COMPETENCIES - Prior full-time experience in finance, data science, or ML engineering. - Familiarity with APIs from Bloomberg, CapIQ, FactSet, or Refinitiv. - Exposure to portfolio optimization, risk modeling, or financial time-series. - Skill with git, Docker, and modern orchestration tools (Prefect, Airflow, etc.). - Early-stage startup experience or demonstrated builder mindset. ## LOCATION Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available. ## BENEFITS We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more. Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees. ## WORKING AT POESIS As an early team member, you’ll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You’ll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together. ## About Poesis ## Company Overview - **One-liner**: Poesis is an AI-native investment manager building a foundation model for investing, using modular AI systems to predict market movements and outperform legacy managers. - **Entity Type**: Private (Bootstrapped) - **Headquarters**: Palo Alto, California, United States - **Founded**: Not publicly available - **Founders**: Alex Popa (Founder & CEO), Charles Elkan (Chief Scientist) ## Core Business - **Primary industry**: AI-powered asset management / hedge fund management - **Target customers**: Institutional investors, asset managers, and clients seeking AI-driven alpha generation (B2B) - **Mission or purpose**: “Build up a scale manager that never gets tired, predicts change earlier, and delivers consistent outcomes for clients in a world being reshaped by intelligence.” ## Products & Services - **Large Investment Model (LIM)**: A single AI foundation model that powers every product—predicts markets, constructs portfolios, and manages risk. It is continuously trained on live capital markets data. - **AI Agents**: Teams of modular, specialized agents that execute prediction, portfolio construction, and risk management tasks, democratizing access to alpha. ## Market Standing - **Valuation**: $3 million (estimated, 2025 – per GetLatka) - **Key Metric**: Annual Recurring Revenue of $990K (estimated ARR for 2025 – per GetLatka); bootstrapped with no outside funding - **Notable Investors/Partners**: None (bootstrapped) - **Growth Signals**: Headcount grew 100% YoY (7 employees on LinkedIn, ~9 on other sources); active hiring for Head of Engineering, Machine Learning Engineer, and Quantitative Developer; LinkedIn follower growth +4.3% monthly ## Competitive Advantages - First mover in building a **foundation model specifically for investing** (the Large Investment Model) - Team composed of senior talent from **Capital Group, Goldman Sachs, and Amazon**—combining deep capital markets experience with AI expertise - Modular, agent-based architecture that can rapidly adapt to market changes - Real-world validation through live capital deployment (training on actual trading) ## Strategic Focus - Scale the Large Investment Model to cover more asset classes and geographies - Continue hiring top-tier AI and engineering talent (founding roles for ML engineers, quant developers, and engineering lead) - Deliver consistent, systematic outperformance for clients through AI-native investment strategies ## Why Work Here - **Culture**: Fast-moving startup environment with mentorship and high ownership; “build alongside investors and technologists reinventing the future of finance and AI” - **Work model**: Hybrid (employees work both remotely and on-site; office in Palo Alto, CA) - **Perks**: High-quality dental, vision, and health care; relocation support available - **Visa sponsorship**: No H-1B sponsorship history found - **Engineering focus**: Good learning environment for building production-scale AI systems; roles include founding-level impact ## Sources 1. [poesis.ai](https://poesis.ai/) 2. [LinkedIn – Poesis AI](https://www.linkedin.com/company/poesisai) 3. [Built In – Poesis Inc.](https://builtin.com/company/poesis-inc) 4. [GetLatka – Poesis AI](https://getlatka.com/companies/poesis.ai) 5. [Scoutify – Poesis Careers](https://scoutify.com/companies/poesis/) ## Other roles at Poesis - [Member of Technical Staff | Machine Learning](https://feeny.ai/job/member-of-technical-staff-machine-learning-poesis-san-francisco-m1dn3k2z352e) — San Francisco, CA - [Head of Engineering](https://feeny.ai/job/head-of-engineering-poesis-san-francisco-01h98a2a5hd6) — San Francisco, CA - [Member of Technical Staff | Head of Agentic Platform Engineering](https://feeny.ai/job/member-of-technical-staff-head-of-agentic-platform-engineering-poesis-san-1n53k3b36pzg) — San Francisco, CA