S&P Global provides market intelligence, credit ratings, analytics, and benchmark indices for businesses, investors, governments, and other organizations worldwide. Its services cover finance, commodities, mobility, sustainability, energy transitions, and artificial intelligence, helping customers interpret market developments, assess credit risk, and make informed decisions.
The company delivers these insights through businesses including S&P Global Market Intelligence, S&P Global Ratings, and S&P Dow Jones Indices. Its data-driven products support research, risk analysis, benchmarking, and strategic planning across complex global markets.
Machine Learning Engineer, Kensho — S&P Global
Build production generative AI systems and retrieval-based agents for Kensho, using S&P Global financial data to ground large language model outputs. Develop scalable machine learning solutions from early exploration through deployment and monitoring.
Description
- Develop and deploy machine learning systems for complex business challenges and Kensho products
- Create retrieval-based AI agents that find, validate, and organize data from S&P datasets
- Assess LLM agents and improve performance, latency, memory use, compute efficiency, and feature consistency
- Work with proprietary structured and unstructured data alongside subject matter experts
- Scale and optimize machine learning systems for demand, resource efficiency, and dependable production operation
- Identify technical debt and recommend improvements to system reliability and maintainability
- Plan and deliver machine learning initiatives across Kensho products
- Partner with teams across Data, Product, Design, and Engineering
- Build machine learning features that improve user workflows
- Contribute throughout the machine learning lifecycle, from problem definition and data exploration to deployment and production monitoring
Requirements
- Bachelor’s degree or higher in computer science, engineering, or a related discipline
- At least three years of substantial hands-on industry experience in machine learning, natural language processing, and information retrieval
- Experience designing, launching, and maintaining production systems
- Strong Python skills
- Ability to understand SQL databases and write queries for specific access patterns
- Experience building machine learning pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation
- Experience with machine learning libraries or frameworks for orchestrating large language models, such as LangChain
- Experience with retrieval-augmented generation systems is preferred
- Effective coding, documentation, collaboration, and communication practices
- Strong problem-solving ability and a proactive mindset
- Ability to adapt to a fast-moving, changing work environment
Benefits
- Health coverage supporting mental and physical well-being
- Generous paid time off
- Ongoing learning and career development resources
- Competitive compensation
- Retirement planning
- Continuing education program
- Company-matched student loan contributions
- Financial wellness programs
- Family-friendly benefits and perks
- Retail discounts
- Referral incentive awards