Principal ML Engineer: Build Production-Ready AI (Remote)

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

Job summary

ZoomInfo is a leading Go-To-Mrowth Intelligence Platform that accelerates careers and empowers teams to do their best work. The role focuses on extending the data graph, predicting metrics for under-documented companies, and building robust ML systems in production with emphasis on language processing and evaluation.

You will work on distributed data processing, Python, and SQL, deploying models at scale, and shaping the engineering direction through mentorship and design reviews.

Qualifications

• ML systems in production with technical leadership as an individual contributor.
• Classical ML on large, messy tabular data with feature engineering and applied statistics.
• Production language processing: text classification and information extraction at scale.
• Built and operated LLM agents or multi-step systems in production with tool/context design and evaluation.

Responsibilities

• Extend ZoomInfo's data graph into the long tail of companies, 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 whether two records describe the same company or person, measuring merge and split errors.
• Infer buying intent from multilingual, noisy text to feed propensity scoring and recommendations.
• Build agents that research companies and cite sources, and design evaluations that separate correct results from imperfect ones.
• Distill large models into smaller ones for cost-effective deployment across the dataset.
• Take ambiguous, high-stakes problems from undefined to shipped, setting technical direction.

Skills

ML in production

Python

SQL

Language processing

Feature engineering

Experiment design

Adversarial defense

Tools

PyTorch

Job description

ZoomInfo is a leading Go-To-Mrowth Intelligence Platform that accelerates careers and empowers teams to do their best work. The role focuses on extending the data graph, predicting metrics for under-documented companies, and building robust ML systems in production with emphasis on language processing and evaluation.

You will work on distributed data processing, Python, and SQL, deploying models at scale, and shaping the engineering direction through mentorship and design reviews.