Senior ML Engineer — Remote, End-to-End Production

ZoomInfo Technologies LLC; Bethesda, Waltham, Vancouver (MD, MA, WA); Hybrid; USD 128,000 - 201,000; Full time

Benefits offered by this job

Remote-friendly

Job summary

ZoomInfo is hiring a Senior ML Engineer to own end-to-end ML systems, from data to product surfaces. You will deploy language processing at scale, build LLM-driven agents, and partner with engineers to improve results and cost efficiency.

You will work with Python and SQL in distributed data pipelines, apply statistics to model evaluation, and use PyTorch for training and inference. This role offers remote-friendly options and a competitive US base salary.

Qualifications

• Must have taken ML systems to production and owned them post-launch.
• Classical ML expertise beyond language models, incl. supervised learning and feature engineering on large tabular data.
• Experience deploying language processing at scale: text classification, information extraction, and entity linking.
• Built LLM agents or multi-step systems in production with tool/context design and failure analysis.

Responsibilities

• Extract leadership, locations, and products from company websites and estimate headcount/revenue.
• Determine if two records describe the same company or person; assess false merges/splits.
• Infer buying intent from multilingual text to feed propensity scoring and recommendations.
• Build research agents that cite sources with evaluation systems behind them.
• Train small models and own quantization and serving.

Skills

ML in production

Classical ML

Feature engineering

Applied statistics

Language processing

LLM agents

Python

SQL

Distributed processing

AI coding tools

Tools

PyTorch

LLM tooling

Git

Job description

ZoomInfo is hiring a Senior ML Engineer to own end-to-end ML systems, from data to product surfaces. You will deploy language processing at scale, build LLM-driven agents, and partner with engineers to improve results and cost efficiency.

You will work with Python and SQL in distributed data pipelines, apply statistics to model evaluation, and use PyTorch for training and inference. This role offers remote-friendly options and a competitive US base salary.