Machine Learning Engineer II

Kensho is S&P Global’s hub for AI innovation and transformation. With expertise in machine learning, natural language processing, and data discovery, we develop and deploy novel solutions to innovate and drive progress at S&P Global and its customers worldwide. Kensho's solutions and research focus on business and financial generative AI applications, agents, data retrieval APIs, data extraction, and much more. We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization) ML role with a strong emphasis on developing and orchestrating intelligent agent frameworks, designing novel and robust retrieval methods, validating AI-generated outputs, and building scalable systems that connect data to actionable insights.

Responsibilities

Solve unique challenges in agentic design and LLM orchestration, including context engineering, data access patterns, memory management, and evaluation of agent performance to ensure they meet user needs effectively; Participate in all stages of the ML lifecycle, from problem framing and data exploration to model experimentation, deployment, and monitoring in production, ensuring the continuous improvement and optimization of our Agentic Systems; Leverage unique proprietary unstructured and structured datasets, applying advanced NLP techniques to extract insights and build solutions that drive business value; Work closely with Data, Product, Design, and Engineering teams to design and develop Agents to enhance user experiences and meet business objectives; Collaborate closely with the ML Operations team to create automated solutions for managing the entire ML systems lifecycle, from initial technical design to seamless implementation.

Requirements

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, with a strong focus on practical applications; Experience with all stages of the ML life-cycle including designing and experimenting to deploying and maintaining production systems; Strong proficiency in Python, with a solid understanding of best practices in software development; Experience working with machine learning libraries and frameworks for agent orchestration, such as LangGraph, pydanticAI, etc.; Experience in agentic design, understanding user interactions, and evaluating agent performance to enhance user experiences; 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.

Benefits

Medical, Dental, and Vision insurance; 100% company paid premiums; Unlimited Paid Time Off; 26 weeks of 100% paid Parental Leave (paternity and maternity); 401(k) plan with 6% employer matching; Generous company matching on donations to non-profit charities; Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences; Plentiful snacks, drinks, and regularly catered lunches; Dog-friendly office (CAM office); Bike sharing program memberships; Compassion leave and elder care leave; Mentoring and additional learning opportunities; Opportunity to expand professional network and participate in conferences and events.