Senior Machine Learning Engineer

Overview

Job Purpose

As a Senior Machine Learning Engineer in NYSE's Data Science, ML, and AI team, you will design, build, and deploy machine learning systems to power intelligent decision-making across the exchange. You will work on a diverse set of problems - from structured prediction and anomaly detection to retrieval-augmented generation - using both classical and modern ML approaches. You will be expected to leverage AI-assisted development tools (e.g. ChatGPT, GitHub Copilot) to accelerate iteration, improve reproducibility, and enhance team productivity.

Responsibilities

• Develop and deploy ML models for structured and unstructured data, including supervised, unsupervised, and generative tasks
• Build production-grade pipelines for model training, evaluation, and deployment, integrating with NYSE's data infrastructure
• Design and operationalize RAG pipelines using LangChain and vector databases where appropriate
• Build and optimize ML microservices using FastAPI, Docker, and Kubernetes; ensure observability, scalability, and cost-efficiency
• Track and manage ML experiments and artifacts using tools such as MLflow
• Define, monitor, and improve performance metrics for deployed ML systems (e.g. accuracy, latency, coverage, user satisfaction)
• Use AI assistants for code generation, testing, and documentation
• Collaborate with stakeholders across engineering, data, and product teams to align technical efforts with business goals
• Stay current with research and industry trends in machine learning and AI, and evaluate applicability to NYSE use cases

Knowledge and Experience

• M.S. or Ph.D. in ML, AI, or related field
• 5+ years of experience in software engineering, including 3+ years building and deploying machine learning models
• Proficiency in Python, including experience with FastAPI and asynchronous programming
• Strong understanding of ML fundamentals (e.g. model evaluation, feature engineering, regularization, bias/variance tradeoffs)
• Experience with modern ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) and model lifecycle tools (e.g. MLflow)
• Familiarity with GenAI/NLP stacks including Hugging Face, OpenAI APIs, and LangChain
• Experience with vector databases (e.g. Pinecone, FAISS) and unstructured data pipelines
• Comfort using GenAI tools (e.g. ChatGPT, GitHub Copilot) to enhance development productivity
• Strong communication skills, with the ability to explain technical concepts to diverse audiences

Preferred Knowledge and Experience

• Exposure to financial market data and its unique properties (e.g. order books, time-series behavior, microstructure)
• Peer-reviewed publications in related fields

New York Base Salary Range

The expected base salary for this role, if located in New York, is between $150,000 - $200,000 USD. The base salary range does not include Intercontinental Exchange's incentive compensation. While we provide this range as general guidance, at ICE we compensate employees based on the skillset and experience of the individual. Regular full-time ICE employees are eligible for a suite of competitive employee benefits, including healthcare coverage (medical, dental and vision), a 401(k) plan, life insurance, time off, and paid leave for qualifying circumstances.

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Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.