Sr. Machine Learning Engineer

At Pitch Book, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We’re deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.

Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there’s going to be some ambiguity along the way, but we excel when we challenge ourselves. We’re willing to take risks, fail fast, and do it all over again in the pursuit of excellence.

If you have a good attitude and are willing to roll up your sleeves to get things done, Pitch Book is the place for you.

About the Role

As a member of the Product and Engineering team at Pitch Book, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve.

Join our team and grow with us!

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI‑powered features that extract meaningful insights from Pitch Book’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands‑on approach to designing, building, and optimizing ML solutions that power user‑facing features on the Pitch Book Platform.

You will be deeply involved in the end‑to‑end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.

Your contributions will help unlock unique value for Pitch Book customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources, and applying ML to enrich our datasets with predictive and generative intelligence. As a senior engineer, you will take ownership of key technical components and ensure that our systems meet the highest standards of performance, reliability, and security.

Primary

Job Responsibilities

• Deliver high‑impact AI and ML capabilities that drive insight generation on the Pitch Book Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities.

• Provide hands‑on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high‑performance systems that meet production‑grade reliability and efficiency standards.

• Support a culture of technical excellence by mentoring peers, sharing knowledge, and participating in code and design reviews. Promote innovation and continuous improvement through collaborative engineering practices.

• Build and optimize models that leverage…