New opportunity

Machine Learning Engineer II

S&P Global · New York; Cambridge, United States

About this role

Kensho, S&P Global’s AI innovation hub, seeks a mid-level Machine Learning Engineer to build agentic AI experiences using financial data. The role spans experimentation through production and focuses on agent frameworks, robust retrieval, validation of AI-generated outputs, and scalable systems that turn data into actionable insights. The position lists New York, New York, and Cambridge, Massachusetts.

Responsibilities

  • Design and orchestrate agents for complex report generation, deep research, and other interactions with financial data. Address context engineering, data access, memory management, LLM orchestration, and agent-performance evaluation.
  • Develop methods for retrieving and synthesizing structured and unstructured data through natural-language interfaces; apply NLP to proprietary datasets.
  • Work across the ML lifecycle, including problem framing, data exploration, experimentation, deployment, production monitoring, and improvement. Partner with Data, Product, Design, Engineering, and ML Operations teams on agent experiences and ML lifecycle automation.

Requirements

  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field, plus 3+ years of hands-on industry experience in machine learning, NLP, and information retrieval systems.
  • Experience designing, experimenting with, deploying, and maintaining production ML systems; strong Python proficiency and software-development practices. Experience with agent-orchestration frameworks such as LangGraph or pydanticAI, agentic design, user interactions, and agent evaluation.
  • Effective coding, documentation, collaboration, communication, and problem-solving skills; ability to adapt to a fast-paced environment.

Tools and compensation: The team uses technologies spanning textual RAG, semantic search, LangGraph, Transformers, PyTorch, data exploration and storage tools, and deployment and MLOps tools. The anticipated base salary range is $140,000–$180,000; the role is also eligible for an annual incentive bonus and equity plans. Listed benefits include company-paid medical, dental, and vision premiums, unlimited paid time off, 26 weeks of paid parental leave, a 401(k) with 6% employer matching, and education assistance.

Skills for this role

Machine LearningNatural Language ProcessingInformation RetrievalPythonAI AgentsAgent OrchestrationLLM OrchestrationContext EngineeringAgent EvaluationSemantic SearchRetrieval-Augmented GenerationLangGraphpydanticAITransformersHugging FaceLightGBMPyTorchscikit-learnXGBoostJupyterMatplotlibPandasWeights & BiasesLangfuseApache SparkAWS AthenaDVCLabelboxOpenSearchPostgreSQL/pgvector

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