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AI​/ML Lead

Job in New York, New York County, New York, 10261, USA
Listing for: Tradeweb
Full Time position
Listed on 2026-07-15
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 250000 USD Yearly USD 150000.00 250000.00 YEAR
Job Description & How to Apply Below
Location: New York

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.

Tradeweb Markets LLC ("Tradeweb") is proud to be an EEO Minorities/Females/Protected Veterans/Disabled/Affirmative Action Employer.

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
    • Enable adaptive learning based on performance outcomes across different market or operational conditions
  • Benchmarking & Data-Driven Insights
    • Collaborate with data and quantitative teams to develop anonymized benchmarking models
    • Define statistical methodologies for performance comparison and optimization
    • Ensure privacy, aggregation, and data governance standards are met
    • Translate complex analytics into actionable outputs within AI-driven systems
  • Conversational Analytics
    • Enable natural language interaction with complex datasets
    • Build systems that interpret user queries, retrieve relevant data, and generate accurate, synthesized insights
    • Support use cases such as performance analysis, comparisons, and trend identification through conversational interfaces
Qualifications
  • 5+ years of experience in applied ML or AI engineering, with at least 2 years working directly with large language models in production
  • Deep hands‑on experience with LLM integration — prompt engineering, tool use, structured output, evaluation frameworks, and hallucination mitigation
  • Strong Python — this is the primary development language for the agent layer and the SDK
  • Experience building systems that translate unstructured natural language into structured, actionable outputs in a production environment
  • Comfort working in a regulated industry where every model output needs to be explainable and auditable
  • Ability to own a technical workstream end‑to‑end — architecture decisions, implementation, and quality bar
Strongly Preferred
  • Experience in financial services, fintech, or trading technology
  • Familiarity with fixed income markets, electronic trading workflows, or execution analytics
  • Experience with transaction cost analysis or execution quality measurement
  • Prior work integrating AI/ML models with real‑time market data
  • Experience building recommendation or optimization systems on proprietary datasets
Benefits
  • Health Insurance
    :
    Highly competitive medical, dental, and vision programs
  • Hybrid Environment
    :
    Our employees have the flexibility of working in the office and from home.
  • Health Care and Dependent Care Flexible Spending Accounts
    :
    You may elect to set aside pre‑tax earnings to pay for eligible health care and dependent day care expenses for you and your eligible family members.
  • Maven Family Building Benefit
    :
    Maven offers support for fertility and preconception; pregnancy and post‑partum; adoption; surrogacy…
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