Job Summary:
PitchBook, a Morningstar company, is dedicated to innovation and collaboration. They are seeking a Machine Learning Engineer to develop AI-powered features that extract insights from structured and unstructured data, focusing on natural language processing and machine learning solutions.
Responsibilities:
• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook 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
• Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best practices
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Mathematics, Data Science, or related technical field, advanced degrees are preferred
• 2+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact
• Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future
Preferred:
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred
Company:
PitchBook offers financial data and tools on companies, deals, investors, and markets to support sales and business development. It is a sub-organization of Morningstar. Founded in 2007, the company is headquartered in Seattle, USA, with a team of 1001-5000 employees. The company is currently Late Stage.