Senior ML Architect: Data Graph & AI Agents

ZoomInfo Technologies LLC; Waltham (MA); On-site; USD 193,000 - 303,000; Full time

Job summary

ZoomInfo is hiring a Principal Machine Learning Engineer to set technical direction for hard problems like extending the data graph, entity resolution, and buying‑intent extraction. You will own outcomes end to end, choosing ML methods and language models as needed.

You will lead production ML systems, battle-test at scale, and mentor others while delivering measurable impact across multilingual data pipelines and data graphs.

Qualifications

• You have taken machine learning systems to production and led design reviews as an IC.
• Classical ML, statistics, and feature engineering on large messy data with experiments and calibrated scores.
• Production language processing including text classification and information extraction at scale.
• Built and operated LLM agents or multi-step systems in production with tool/context design and evaluation.
• Proficient in production Python and strong SQL with distributed data processing.

Responsibilities

• Extend the data graph into the long tail of companies by extracting leadership, locations, and products from websites.
• Predict headcount and revenue for under-documented companies using gradient-boosted trees and regression with missing inputs.
• Determine if two records describe the same company or person, minimizing merge/split errors.
• Infer buying intent from multilingual, noisy text to feed propensity scoring and recommendations.
• Build agents that research companies with sources and design proper evaluations.

Skills

Production ML

Python

SQL

Distributed processing

Mentoring

Tools

PyTorch

LLM Agents

Job description

ZoomInfo is hiring a Principal Machine Learning Engineer to set technical direction for hard problems like extending the data graph, entity resolution, and buying‑intent extraction. You will own outcomes end to end, choosing ML methods and language models as needed.

You will lead production ML systems, battle-test at scale, and mentor others while delivering measurable impact across multilingual data pipelines and data graphs.