Sr. Machine Learning Engineer (AI/ML)

TL;DR

Sr. Machine Learning Engineer (AI/ML): Deliver AI-powered features that extract meaningful insights from PitchBook’s structured and unstructured data with an accent on end-to-end ML model architecture, training, deployment, and operational maintenance. Focus on NLP, generative AI, LLMs, and scalable data systems while solving production-grade reliability, performance, and responsible AI challenges.

Location: Seattle, Washington, United States

Salary: $170,000-$240,000 annually; Target annual bonus: 10%

Company

hirify.global builds data-driven products for financial professionals as part of Morningstar.

What you will do

• Deliver high-impact AI/ML capabilities that drive insight generation on the PitchBook Platform.
• Design, build, deploy, and optimize production AI/ML models and services for NLP, summarization, semantic search, classification, and prediction.
• Own end-to-end development and operationalization of ML models, including architecture, training, deployment, monitoring, evaluation, and compliance.
• Build and integrate models using classifiers, transformers, and LLMs into scalable, high-performance data and AI infrastructure.
• Collaborate with engineering, product management, and data collection teams to ensure models use high-quality data and align with business goals.
• Mentor peers and contribute to code/design reviews, documentation, and candidate evaluation.

Requirements

• 6+ years of experience in software engineering or machine learning engineering focused on AI/ML applications for insight generation, summarization, semantic search, and prediction.
• Hands-on expertise in NLP and machine learning, including classifiers, transformer models, and LLMs; experience with scikit-learn, pandas, numpy, TensorFlow, and PyTorch.
• Experience delivering production-grade GenAI/LLM-based systems with measurable business impact.
• Strong skills in Python and SQL; experience with scalable data pipelines and distributed systems (e.g., Apache Kafka, Airflow, Snowflake).
• Practical experience with cloud-native development, containerization, and orchestration (e.g., Docker, Kubernetes).
• Must be authorized to work in the United States without visa sponsorship now or in the future.

Culture & Benefits

• Comprehensive health benefits plus additional medical wellness incentives; STD/LTD/AD&D and life insurance.
• Paid sabbatical after four years; paid family and paternity leave.
• Annual educational stipend and tuition reimbursement; CFA exam stipend.
• Generous vacation, sick, and volunteer days; employee assistance program.
• 401k match and shared ownership employee stock program; monthly transportation stipend.
• Role is expected to be in the office 5 days a week.

Hiring process

• Technical evaluation of candidates and collaboration-based interviews with cross-functional stakeholders.
• Assessment of ML engineering depth, production experience, and ability to contribute to architecture and reviews.