Machine Learning Engineer

S&P Global

ML Engineer developing and deploying state-of-the-art GenAI systems at S&P Global. Collaborating across teams to ensure robust ML solutions that drive business advancements.

Posted 7/1/2026full-timeHyderabad • 🇮🇳 IndiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Develop Advanced ML Systems: Create, refine, and deploy machine learning systems that solve complex business problems and power Kensho products.
Build Retrieval-Driven AI Agents: Design AI agents that fetch, validate, and structure data from S&P datasets, ensuring answers produced by LLMs are grounded in S&P’s data universe.
Evaluate LLM-based Agents: Identify and resolve performance gaps in both online and offline settings, addressing issues such as performance, latency, memory usage, compute efficiency, and feature consistency.
Work With Domain Specific Data: Leverage proprietary structured and unstructured datasets, deep dive to have domain understanding, work with Subject Matter Experts (SMEs).
Scale ML Applications: Optimize and scale ML systems to support high demand, efficient resource utilization, and reliable production behavior.
Reduce Technical Debt: Proactively identify areas of the stack that can be improved, and propose solutions that strengthen reliability and maintainability.
Taking Initiative: Scope, plan, and execute ML initiatives that develop core capabilities across Kensho products.
Collaborate Across Teams: Work closely with Data, Product, Design, and Engineering teams to ensure smooth operations and contribute to long-term product vision.
Improve User Experiences: Partner with Product and Design to develop ML-driven functionality that enhances user workflows and aligns with business needs.
Drive the ML Lifecycle: Engage in all phases of the ML lifecycle, from problem framing and data exploration to model deployment and production monitoring, ensuring continuous improvement.

Requirements

What you’ll need

Bachelor's degree or higher in Computer Science, Engineering, or a related field.
3+ years of significant, hands-on industry experience with machine learning, natural language processing (NLP), and information retrieval systems, including designing, shipping, and maintaining production systems.
Strong proficiency in Python.
Experience reading and understanding SQL databases and writing queries for specific access patterns.
Proven experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation.
Demonstrated effective coding, documentation, collaboration, and communication habits.
Strong problem-solving skills and a proactive approach to addressing challenges.
Ability to adapt to a fast-paced and dynamic work environment.
Experience working with machine learning libraries/frameworks for Large Language Model (LLM) orchestration, such as Langchain. (Preferred)
Experience working with RAG based system.

Benefits

Comp & perks

Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

ATS Keywords

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Hard Skills & Tools

Machine LearningInformation Retrieval SystemsData ProcessingModel DeploymentPerformance EvaluationFeature ConsistencyTechnical Debt ReductionML Lifecycle ManagementData ExplorationExperimentation

Soft Skills

Problem-SolvingProactive InitiativeCollaborationEffective CommunicationAdaptability