PitchBook · 1 day ago
Machine Learning Engineer
Seattle, WA
Full-time
Onsite
Entry, Mid Level
$125K/yr - $180K/yr
2+ years expPitchBook, a Morningstar company, is seeking a Machine Learning Engineer to join their Product and Engineering team. The role involves delivering AI-powered features that extract insights from structured and unstructured data, requiring expertise in advanced data analytics and machine learning, particularly in natural language processing and generative AI.
AnalyticsFinanceVenture Capital
No H1B
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
Qualification
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
Benefits
Comprehensive health benefits
Additional medical wellness incentives
STD, LTD, AD&D, and life insurance
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
Matching gifts program
Employee resource groups
Subsidized emergency childcare
Dependent Care FSA
Company-wide events
Employee referral bonus program
Quarterly team building events
401k match
Shared ownership employee stock program
Monthly transportation stipend
Company
PitchBook
PitchBook offers financial data and tools on companies, deals, investors, and markets to support sales and business development.
1001-5000 employees
Funding
Current Stage
Late StageTotal Funding
$13.8MKey Investors
Morningstar
2016-10-14Acquired
2016-01-27Series B· $10M
2009-09-25Series A· $3.8M
Leadership Team
Nizar Tarhuni
Executive Vice President, Research & Market Intelligence
Brett Kaluza
Chief Customer Officer
Recent News
2026-01-17
2025-12-19
Company data provided by crunchbase