Machine Learning Engineer

As an Applied AI Engineer embedded within the Office of the CEO and President (OCEO/OOP), you will serve as a high-impact builder driving the future of AI-enabled business transformation at Pagaya Working at the intersection of business strategy, data architecture, and modern artificial intelligence, you will build and deploy practical, high-value AI solutions, automations, and intelligent agents that modernize internal workflows Starting within the OCEO/OOP to address high-visibility executive priorities, your work will quickly expand to partner with key business functions across Capital Markets, Finance, and broader Operations Combining a strong background in Business Intelligence (BI) with hands-on AI engineering capabilities, you will translate complex financial workflows into durable, scalable AI systems that elevate operational speed and analytical precision across the company Embedded AI Development: Act as the primary technical builder, advisor, and problem-solver for AI-enabled workflow transformations - starting in the OCEO/OOP and expanding into Capital Markets, Finance, and key operational units Workflow Automation & Agentic Systems: Identify manual, repeated, or data-dense business processes and build production-ready AI tools, customized copilots, and agentic workflows to streamline execution BI & Data Integration: Leverage a robust background in Business Intelligence and data analysis to connect LLMs, foundation models, and AI agent frameworks directly into Pagaya’s data infrastructure, dashboards, and financial models Cross-Functional Execution: Work closely with business leadership, financial analysts, and capital markets teams to translate ambiguous business problems and complex financial data into practical, user-friendly technical solutions Rapid Prototyping & Scale: Design, iterate, and deploy prototypes rapidly based on stakeholder feedback, while adhering to enterprise standards for data security, governance, and responsible AI usage Enablement & Documentation: Templatize and document solutions to enable scalable reuse across departments; lead walkthroughs and light enablement to drive active user adoption across technical and non-technical teams Business Intelligence Core: Strong mastery of SQL, data modeling, BI tools (e.g., Tableau, PowerBI, Looker), and experience processing, analyzing, and structuring large data setsModern AI Tooling & Frameworks: Hands-on experience with modern LLM APIs/ecosystems (OpenAI, Claude, Gemini), agentic orchestration frameworks, RAG (Retrieval-Augmented Generation) architectures, and enterprise AI platformsExperience: 4+ years of experience in data engineering, business intelligence, or software engineering with demonstrated hands-on experience building applied AI solutions, internal tools, or AI-driven automationsCommunication & Stakeholder Management: Exceptional written and verbal communication skills with a proven track record of distilling technical and financial concepts for non-technical leadership and cross-functional teamsPreferred: Prior exposure to financial services, structured finance, fixed income, or capital markets workflows is a strong plusAdaptability & Drive: An entrepreneurial mindset with the ability to manage multiple complex, fast-paced projects simultaneously, delivering meticulously accurate, self-audited work within tight deadlinesTechnical & Coding Proficiency: Advanced proficiency in Python (or JavaScript/TypeScript) for data manipulation, backend scripting, and rapid software prototyping; comfort generating, debugging, and refactoring AI-generated codeEducation: Bachelor’s degree in Computer Science, Data Science, Information Systems, Finance, Engineering, or an equivalent quantitative discipline required #J-18808-Ljbffr