Machine Learning Engineer

PitchBook Data helps power better decisions with AI and machine learning built for the PitchBook Platform. Join the AI & ML (Insights) team in Seattle, WA (onsite) to deliver end-to-end models and services that turn structured and unstructured data into meaningful insights across NLP, generative AI, and LLM-based solutions.

What you’ll work on

This role focuses on building production-ready intelligence for the platform, from design through operationalization. You’ll develop scalable, high-performance AI/ML systems and help translate experimentation and research into practical solutions that enhance PitchBook’s AI capabilities.

• Deliver AI and ML capabilities that drive insight generation on the PitchBook Platform and align to team strategic priorities
• Design, build, and deploy AI/ML models and services across NLP, summarization, semantic search, classification, and prediction
• Build and optimize models using classifiers, transformers, LLMs, and other NLP techniques, then integrate them into the broader AI/ML infrastructure with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support product goals
• Explore and experiment with emerging GenAI, NLP, and search technologies, then translate research into implemented improvements
• Support model transparency with monitoring, evaluation, and compliance, while maintaining high standards for security, data integrity, and responsible AI use
• Contribute to technical evaluation of candidates and help onboard new team members through documentation, pairing, and knowledge sharing
• Apply Agile, Lean, and Fast-Flow principles to support efficient model development and deployment cycles
• Role model company values and participate in requested company initiatives and projects

Technologies you’ll use

Work across a modern stack including Python, SQL, Java, Scala, and core libraries such as scikit-learn, pandas, NumPy, TensorFlow, PyTorch, plus AI tooling like LangChain, LangSmith, LangGraph. For data and pipelines: Apache Kafka, Airflow, Snowflake. For delivery and infrastructure: Docker, Kubernetes.

What we’re looking for

• 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 for insight generation, summarization, semantic search, and prediction
• Authorization to work in the United States without visa sponsorship now or in the future

Preferred qualifications

• Hands-on expertise in NLP and machine learning with experience in classifiers, transformer models, and LLMs, including 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 LangSmith and LangGraph) used in production environments
• Experience building scalable data pipelines and distributed systems using Apache Kafka, Airflow, and data platforms like Snowflake
• Strong Python and SQL skills; knowledge of Java or Scala is a plus
• Practical experience with cloud-native development, containerization, and orchestration using Docker and Kubernetes
• Ability to solve complex technical problems, contribute to architectural decisions, and deliver reliable, high-performance solutions
• Strong communication and cross-functional collaboration, including work with product managers, engineers, and data scientists in globally distributed teams
• Experience in fast-paced, data-driven environments; fintech or financial data platforms are a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred

Compensation

Annual base salary: $125,000 to $180,000. Target annual bonus: 10%.

Benefits

• Comprehensive health benefits, plus 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, tuition reimbursement, and a 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 and employee resource groups
• Subsidized emergency childcare and Dependent Care FSA
• Company-wide events and quarterly team building events
• Employee referral bonus program
• 401k match and a shared ownership employee stock program
• Monthly transportation stipend

Working conditions

• Expected to be in the office 5 days a week
• Standard office setting; employees use a PC and phone on an ongoing basis throughout the day
• Limited corporate travel may be required to remote offices or other business meetings and events