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S&P Global

Delivers credit ratings, market data, indices

Lead AI/ML Engineer

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 10 years of experience designing, building, and deploying production-grade AI, machine learning, or data-driven solutions in AWS cloud environments, including end-to-end ownership from solution architecture through live operation.
  • At least 5 years of Python development and production use of at least one machine learning framework—TensorFlow, PyTorch, or scikit-learn—in end-to-end model training, evaluation, and deployment pipelines.
  • At least 3 years of Java application development using Spring Boot in microservices architectures, and at least 3 years deploying and managing containerized workloads using Docker and Kubernetes in cloud-hosted environments, with active use of Git-based continuous integration and continuous delivery workflows.
  • Demonstrated delivery of at least two production AI systems incorporating deep learning, natural language processing, or Generative AI techniques; applied SQL-based management of structured and unstructured datasets at enterprise scale; and hands-on development using agentic AI frameworks or autonomous workflow architectures.
  • Demonstrated use of AI-assisted development tools such as GitHub Copilot, Cursor, or Claude Code across at least two shipped production projects, integrated within a structured team-based software development lifecycle.
  • The role is limited to persons with indefinite right to work in the United States.

Responsibilities

  • Architect and own end-to-end delivery of scalable machine learning and Generative AI solutions, from requirements definition with senior business stakeholders through production deployment on AWS.
  • Design and build reusable AI platforms, model evaluation frameworks, and performance optimization tooling used across the Ratings organization.
  • Apply agentic AI frameworks, large language model fine-tuning, and retrieval-augmented generation to credit ratings datasets to produce data-driven insights.
  • Lead technical research and adoption of emerging AI and machine learning technologies to improve the quality, scalability, and performance of existing Ratings analytics solutions.
  • Partner with data scientists, software engineers, and business analysts to translate analytical requirements into production-grade solutions delivered within agreed timelines.
  • Define and champion AI engineering best practices, reusable capability frameworks, and technical standards for the Data Services team.

Desired Qualifications

  • Delivered at least one production or near-production agentic AI system using LangChain, LangGraph, CrewAI, ADK, or Strands.
  • At least 2 years of hands-on experience implementing graph databases such as Neo4j or Amazon Neptune, or graph-based algorithms within data engineering or machine learning feature pipelines.
  • Working proficiency in at least one front-end technology—React, JavaScript, or HTML—demonstrated through integration of machine learning model outputs into a user-facing application.
  • At least 2 years of data engineering experience, including pipeline development, feature engineering, and data preparation for machine learning model training in a cloud environment.
  • Hands-on experience designing or operating data lakes or AI-ready data platforms such as AWS Lake Formation, Databricks, or Snowflake at enterprise scale.
  • Experience deploying machine learning solutions using Apache Spark or Hadoop on datasets exceeding 1 TB in a distributed cloud environment.
  • At least 2 years applying AI-native software development lifecycle practices, including automated model evaluation pipelines, experiment tracking such as MLflow or Weights & Biases, and model versioning within a team-based continuous integration and continuous delivery workflow.

About the Company

S&P Global

Delivers credit ratings, market data, indices

S&P Global provides financial information and analytics for investors, corporations, and governments, including credit ratings, market data, and indices. It compiles large financial data, conducts research, and offers analytics, ratings, and benchmarks accessed via subscriptions, licenses, or transaction-based services. The company differentiates itself with an integrated suite that covers ratings, data, analytics, indices, and ESG solutions across global markets, backed by well-known brands. Its goal is to help clients make informed decisions, manage risk, and drive growth while prioritizing corporate responsibility.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1917

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