AI/ML Lead

Tradeweb is a global leader in electronic trading across asset classes. As financial markets become increasingly interconnected, our technology enables efficient, multi-asset trading on a global scale. We serve more than 3,000 clients in more than 85 countries, including many of the world’s largest banks, asset managers, hedge funds, insurers, corporations, and wealth managers. Creative collaboration and sharp client focus have helped fuel our organic growth. We facilitated average daily trading volume (ADV) of more than $2.8 trillion over the past four fiscal quarters, topping $3.3 trillion in ADV for the first quarter of 2026. Since our IPO in 2019, Tradeweb has completed four acquisitions and doubled our revenues – and 2025 was our 26th consecutive year of record revenues. Tradeweb plays a central role in modernizing market structure by developing innovative trading protocols, embedding analytics into execution, and building technology infrastructure that supports the convergence of traditional and digitally native financial markets. Tradeweb is a great place to work, recognized in 2025 by Forbes as one of America's Best Companies and by U.S. News & World Report as one of the Best Financial Services Companies to Work For. Tradeweb Markets LLC ("Tradeweb") is proud to be an EEO Minorities/Females/Protected Veterans/Disabled/Affirmative Action Employer. Workplace Posters | U.S. Department of Labor Group Details We are seeking an experienced AI/LLM Product Engineer to design and build intelligent, language-driven systems that translate user intent into structured execution workflows. This role sits at the intersection of large language models, data science, and electronic trading, with a focus on building scalable, accurate, and explainable AI-powered decision systems. Job Responsibilities LLM Integration & Prompt Architecture Design and own the integration between conversational AI agents and external large language model APIs Develop and continuously refine prompt architectures that translate natural language into structured system actions and parameters Build confirmation and validation flows to ensure outputs are accurate, explainable, and auditable Establish and maintain high standards for interpretation accuracy at scale Intent Parsing & Natural Language Processing Build systems that reliably map user instructions into structured parameters across varied phrasing, domains, and strategies Define evaluation frameworks to measure and improve NLP performance Handle ambiguity, edge cases, and fallback scenarios while maintaining user trust Intelligent Recommendation Systems Design and develop engines that proactively recommend optimized configurations or actions based on historical behavior, real-time conditions, and benchmark data Incorporate multiple data sources to generate insights that outperform manual decision-making Continuously improve recommendation quality through feedback and iteration Feedback Loops & Model Improvement Build mechanisms that leverage post-action or post-trade analytics to refine system recommendations over time #J-18808-Ljbffr Tradeweb Markets