Machine Learning Operations Engineer

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. At Kensho, we hire talented people and give them the autonomy and support needed to build amazing technology and products.

We collaborate using our teammates' diverse perspectives to solve hard problems. Our communication with one another is open, honest, and efficient. We dedicate time and resources to explore new ideas, but always rooted in engineering best practices. As a result, we can innovate rapidly to produce technology that is scalable, robust, and useful.

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. At Kensho, we hire talented people and give them the autonomy and support needed to build amazing technology and products.

We collaborate using our teammates' diverse perspectives to solve hard problems. Our communication with one other is open, honest, and efficient. We dedicate time and resources to explore new ideas but always rooted in engineering best practices. As a result, we can innovate rapidly to produce technology that is scalable, robust, and useful.

The MLOps team is the de facto ML platform team  team’s mission is critical: empower our ML engineers with state-of-the-art processes, tooling, and infrastructure to iterate quickly, build reliably, and identify potential production issues early. We sit at the intersection of infrastructure and ML, and work closely with all our ML teams (ML Product teams, R&D, …) and our infrastructure teams (Core Infra, SRE, Security).

We are a small and high-leverage team: our work practically touches every AI project  balance pragmatic platform development with hands-on exploration at the frontier: building agentic applications ourselves, contributing to open-source tools, and defining what a mature agentic platform looks like before the industry has settled on the answers. You’re equally likely to find us at a top ML conference (NeurIPS, ICLR, ICML) and at major software and infra conferences (Amazon Re:invent, PyCon).

To illustrate the point, within the same month, the same engineer went from reimplementing a prompt optimization research paper to shipping prometheus alerts.

As an MLOps Engineer, you are a thoughtful, curious, collaborative, and resourceful person passionate about building and supporting a mature ML platform. You are not afraid to dig deep in both infrastructure and ML topics. You’re excited to work on internal tooling enabling ML engineers to iterate faster and build high-quality production-ready models, agents, and products. You love improving the developer experience (including your own!)

and find genuine satisfaction in making engineers more effective, whether by saving engineering hours or amplifying the impact of an engineering organization. You take pride in having a multiplier effect across an engineering team or process, and you enjoy working with multiple teams with different products and workflows.

At Kensho, we hire talented people and give them the autonomy and support needed to build amazing technology and products. We support our…