Machine Learning Engineer

About the role

The role is part of the Product and Engineering team at PitchBook, a Morningstar company. We are a collaborative and innovative environment where we strive to deepen the positive impact on our customers and the company.

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.
• 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.
• 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

• 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.
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus.
• 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.
• Prior exposure to fintech or financial data platforms is a strong advantage.
• Experience working in fast-paced, data-driven environments.
• 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.

Skills

• 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.
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus.
• 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.
• Prior exposure to fintech or financial data platforms is a strong advantage.
• Experience working in fast-paced, data-driven environments.
• 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.

Benefits + Compensation

• Physical Health: Comprehensive health benefits, additional medical wellness incentives, STD, LTD, AD&D, and life insurance.
• Emotional Health: Paid sabbatical program after four years, paid family and paternity leave, annual educational stipend, CFA exam stipend, robust training programs on industry and soft skills, Employee Assistance Program.
• Social Health: Matching gifts program, Employee resource groups, subsidized emergency childcare, Dependent Care FSA, Company-wide events, Employee referral bonus program, Quarterly team building events.
• Financial Health: 401k match, Shared ownership employee stock program, Monthly transportation stipend.

Working Conditions

The role is expected to be in the office 5 days a week. The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.