S&P Global

Machine Learning Engineer

S&P Global
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7 days ago
Bengaluru, India or Hyderābād, IndiaMid Level / Senior
H1B Sponsor

Responsibilities

  • Develop, refine, deploy, and scale machine learning systems for Kensho products.
  • Build retrieval-driven AI agents that fetch, validate, and structure data from S&P Global datasets.
  • Evaluate LLM-based agents across performance, latency, memory usage, compute efficiency, and feature consistency.
  • Work with structured and unstructured domain-specific data and subject matter experts.
  • Improve reliability, maintainability, and production operations while reducing technical debt.
  • Scope, plan, and execute ML initiatives across Kensho products.
  • Collaborate with Data, Product, Design, and Engineering teams on product vision and user workflows.
  • Manage the full ML lifecycle from problem framing and data exploration through deployment, monitoring, and continuous improvement.

Requirements

  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
  • At least 3 years of hands-on industry experience with machine learning, NLP, and information retrieval systems, including designing, shipping, and maintaining production systems.
  • Strong proficiency in Python.
  • Experience reading SQL databases and writing queries for specific access patterns.
  • Experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation.
  • Effective coding, documentation, collaboration, communication, problem-solving, and initiative-taking skills.
  • Ability to adapt to a fast-paced and dynamic work environment.
  • Experience with LLM orchestration libraries or frameworks such as LangChain.
  • Preferred experience with RAG-based systems.

Benefits

  • Health care coverage and wellness benefits.
  • Generous flexible time off.
  • Continuous learning and career development resources.
  • Retirement planning, continuing education, company-matched student loan contributions, and financial wellness programs.
  • Family-friendly benefits and perks.
  • Retail discounts and referral incentive awards.

Tech Stack

AWSDockerDVCJenkinsLightGBMMatplotlibPandasPostgreSQLPythonPyTorchscikit-learnSQLSQLiteXGBoost

Categories

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