Machine Learning Engineering Manager

Role Overview

• Manage, mentor, and develop a team of ML Engineers and Applied ML Scientists, ensuring they are engaged, supported, and set up for long-term success.
• Define technical direction, set priorities, and guide the team in building models, retrieval agents, and ML systems that power Kensho’s GenAI platform and AI toolkits such as Link and NERD.
• Ensure the team follows best practices for building robust, scalable, and maintainable ML solutions, including data pipelines, training workflows, retrieval systems, and model deployment.
• Oversee the development and evaluation of LLM-powered agents and grounded retrieval systems that use trusted S&P datasets to produce accurate, verifiable results.
• Collaborate closely with Product Management and cross-functional leaders to identify opportunities, define problem statements, and align ML initiatives with business objectives.
• Establish strong engineering practices, maintain high code quality, and foster a culture of reliability, observability, and continuous improvement across ML systems.
• Partner with Talent Acquisition to attract, interview, and onboard exceptional ML engineering talent as the ML organization grows.
• Contribute technically in design reviews, code reviews, modeling decisions, and architecture discussions, while empowering the team to own implementation and execution.
• Oversee monitoring, debugging, and performance evaluation of ML systems in production, ensuring reliability and consistent service quality.
• Work with Backend, Infrastructure, Product, and Data teams to ensure ML systems integrate seamlessly into Kensho’s broader platform and applications.

Requirements

• Have 7+ years of industry experience designing, building, evaluating, and maintaining robust and scalable production ML systems.
• Have 2+ years of experience managing ML engineering or applied ML teams.
• Have experience mentoring engineers and scientists, with a long-term mindset toward team development and hiring.
• Have partnered with product managers to define roadmaps, scope problems, and drive user-focused outcomes.
• Have a deep understanding of modern ML system design, including data processing, training, retrieval, evaluation, deployment, and production monitoring.
• Are comfortable leading technical decisions and guiding teams through complex modeling and system design trade-offs.
• Are an effective communicator who can translate between engineering, ML, product, and business stakeholders.
• Are innovation-minded and able to propose creative, practical solutions to ambiguous problems.
• Are a collaborative reviewer and a thoughtful teammate who values clarity, feedback, and shared ownership.
• Are highly organized, results-oriented, and capable of ensuring steady execution while supporting individual growth.
• Measure your success through your team’s success and impact.

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.