Senior ML Engineer: GenAI & NLP for Insights (On‑Site)

PitchBook Data, Inc; Seattle (WA); On-site; USD 170,000 - 240,000; Full time

Benefits offered by this job

Annual wellness incentives

Sabbatical after four years

Educational stipend

Tuition reimbursement

Employee stock program

Monthly transportation stipend

Employee assistance program

Job summary

PitchBook Data, Inc. is seeking a Senior Machine Learning Engineer in Seattle to lead end-to-end AI/ML initiatives on the AI & ML (Insights) team. You will design, train, and deploy NLP models and GenAI solutions that power the PitchBook Platform.

You will work closely with engineers, data scientists, and product managers to deliver scalable, production-grade systems while advancing security and interpretability. This is an in-person role with strong collaboration across teams.

Qualifications

• 6 years minimum of experience in software or ML engineering with AI/ML focus.
• Strong experience in NLP, summarization, semantic search and prediction.
• Authorized to work in the United States without sponsorship now or in future.

Responsibilities

• Deliver AI/ML capabilities that drive insight generation in PitchBook Platform.
• Design, build, and deploy NLP/ML models with production-grade reliability.
• Mentor peers and participate in code/design reviews to raise standards.
• Develop scalable models using transformers and LLMs; integrate with infra.
• Collaborate with cross-functional teams to align with product goals.

Skills

NLP

LLMs

Transformers

Data pipelines

Python

SQL

Distributed systems

Education

Bachelor’s in Computer Science or related

Tools

Python

SQL

TensorFlow

PyTorch

LangChain

Kafka

Airflow

Snowflake

Docker

Kubernetes

Job description

PitchBook Data, Inc. is seeking a Senior Machine Learning Engineer in Seattle to lead end-to-end AI/ML initiatives on the AI & ML (Insights) team. You will design, train, and deploy NLP models and GenAI solutions that power the PitchBook Platform.

You will work closely with engineers, data scientists, and product managers to deliver scalable, production-grade systems while advancing security and interpretability. This is an in-person role with strong collaboration across teams.