PitchBook · 1 day ago
Staff Machine Learning Engineer, Data Collections AI & ML
Seattle, WA
Full-time
Onsite
Lead/Staff
$260K/yr - $325K/yr
8+ years expPitchBook, a Morningstar company, is seeking a Staff Machine Learning Engineer for their Data Collection AI & ML team. The role focuses on designing and deploying advanced AI and machine learning systems to enhance data extraction and enrichment workflows, while collaborating closely with various teams to translate business requirements into impactful AI solutions.
AnalyticsFinanceVenture Capital
Responsibilities
Serve as the key technical leader shaping system design, ML architectures, model lifecycles, and scalable infrastructure for data extraction, document understanding, and structured data enrichment
Architect reusable frameworks and services for LLM-powered extraction, entity recognition and resolution models, and multimodal document processing
Partner with engineering leaders to ensure our systems meet the highest standards of reliability, performance, and cost efficiency
Design and build state-of-the-art ML models using transformers, LLMs, generative models, graph-based approaches, and OCR/Document AI frameworks
Identify opportunities to advance automation and accuracy across our ingestion stack, including entity linking, relationship inference, classification, and anomaly detection
Translate emerging research into practical, production-ready capabilities
Contribute to PitchBook’s growing technical reputation through experimentation, publication, or open-source work
Work closely with Product, Engineering, and Data Operations to ensure AI systems integrate smoothly into human-in-the-loop workflows and downstream pipelines
Provide technical expertise during prioritization discussions, roadmap planning, and long-term strategic design
Elevate engineering excellence through code reviews, design reviews, and technical guidance for ML engineers and scientists
Act as a multiplier by shaping best practices for experimentation, model evaluation, responsible AI, and scalable ML engineering
Guide teams across the organization toward cohesive, reusable, and standards-aligned architectures
Own the lifecycle of mission-critical ML systems from data preparation to deployment, monitoring, and continuous improvement
Ensure strong standards for model governance, explainability, and data integrity across the AI/ML stack
Partner with ML Ops and Platform Engineering teams, along with other partner engineering groups, to maintain high availability, reliability, and robustness for production ML systems
Qualification
Required
Bachelor's or Master's degree in Computer Science, Mathematics, Data Science, or a related technical discipline (Master's degree preferred)
8+ years of experience in machine learning, data science, or AI-focused engineering, with at least 4+ years of experience leading technical teams
Proven success delivering AI-driven data extraction, enrichment, or document understanding systems at scale. Hands-on experience with parameter-efficient fine-tuning methods and expertise in document classification optimization preferred
Deep expertise in natural language processing, document AI, OCR, entity resolution, and large-scale data automation
Strong understanding of modern ML frameworks and infrastructure (e.g., PyTorch, TensorFlow, Hugging Face, LangChain, MLFlow)
Demonstrated ability to define and execute multi-year AI roadmaps with measurable business impact
Strong knowledge of cloud-native architecture, distributed computing, and scalable model deployment
Excellent communication, collaboration, and influencing skills including experience presenting to executive and cross-functional leadership
A track record of fostering technical excellence and innovation across global, multidisciplinary teams
Preferred
Experience in fintech, data platforms, or large-scale information extraction systems preferred
Contributions to the AI/ML research community (e.g., publications, patents, or open-source projects) are 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
H1B Sponsorship
PitchBook has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (4)
2024 (5)
2023 (5)
2022 (3)
2021 (4)
2020 (1)
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
2025-12-19
2025-12-18
Company data provided by crunchbase