Senior Machine Learning Engineer

S&P Global Commodity Insights is looking for an experienced Machine Learning Engineer to join our Data Science & Modelling team.

In this role, you will design, build and productionize machine learning and AI solutions using S&P Global's extensive data and domain expertise.

Responsibilities:

• Design, develop and productionize scalable machine learning and AI solutions for complex business and modelling problems.
• Build robust data and ML pipelines that support the complete lifecycle from data preparation and feature engineering through training, deployment, evaluation and monitoring.
• Develop high-quality, reusable Python software and services that integrate ML capabilities into production applications and analytical platforms.
• Work with large and complex structured and unstructured datasets to improve the quality, accuracy and intelligence of our products and modelling capabilities.
• Apply modern ML techniques, and where appropriate Generative AI, LLMs and agent-based approaches, to solve business and domain problems.
• Establish and apply strong MLOps and software engineering practices, including automated testing, CI/CD, versioning, observability and reproducibility.
• Build solutions using modern cloud and distributed-computing platforms.
• Evaluate model quality and system performance using appropriate quantitative metrics, validation frameworks and monitoring.
• Collaborate closely with data scientists, modelers, data engineers, product teams and energy-domain experts to translate business and modelling requirements into robust technical solutions.
• Investigate emerging ML and AI technologies and identify practical opportunities to apply them within Data Science & Modelling.
• Contribute to engineering standards, architecture decisions, code reviews and technical mentoring across the team.

Requirements:

• 7+ years of professional software development or engineering experience, with strong proficiency in Python.
• Demonstrated experience designing and implementing production-grade machine learning or advanced analytical systems.
• Strong knowledge of software engineering fundamentals, including object-oriented design, modular architecture, testing, clean-code practices and design patterns.
• Strong experience working with SQL and large-scale data platforms.
• Experience building scalable data processing and ML pipelines using technologies such as Apache Spark / PySpark and Databricks or comparable platforms.
• Experience deploying and operating solutions in a cloud environment such as AWS.
• Understanding of the ML lifecycle, including training, validation, deployment, monitoring and model/version management.
• Experience with modern engineering and DevOps practices including Git, automated testing, CI/CD and containerization.
• Ability to design reliable, performant and maintainable systems handling large or complex datasets.
• Strong analytical and problem-solving skills.
• Ability to communicate effectively with both technical and non-technical stakeholders and work successfully in cross-functional Agile teams.
• Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, Data Science or a related quantitative discipline, or equivalent practical experience.

Benefits:

• 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.