Values

The ad says“Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake”
The ad says“Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake”
The ad says“Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes”
The ad says“Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus”
The ad says“Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes”
The ad says“Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus”
The ad says“Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus”
The ad says“Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus”
The ad says“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”
The ad says“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”
The ad says“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”
The ad says“Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus”
The ad says“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”
The ad says“Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake”
The ad says“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”

At PitchBook, 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, PitchBook is the place for you.

About the Role:

As a member of the Product and Engineering team at PitchBook, 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 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 PitchBook’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 PitchBook 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 PitchBook 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.

Primary Job 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

Basic Qualifications:

Bachelor’s degree in Computer Science, Mathematics, or Data Science
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
Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Preferred Qualifications:

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
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
Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
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 at PitchBook:

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
Ability to apply for tuition reimbursement
CFA exam stipend
Robust training programs on industry and soft skills
Employee assistance program
Generous allotment of vacation days, sick days, and volunteer days

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

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

Annual base salary: $125,000-$180,000
Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This 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.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

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