# Principal Machine Learning Engineer **Company**: ZoomInfo **Location**: Waltham, MA **Experience**: senior **Job type**: full-time **Salary**: $192,500-$302,500 USD **Category**: Engineering **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/zoominfo/jobs/8628076002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_749bd0e6-737 ## Description ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. As a Principal Machine Learning Engineer, you will set technical direction for one or more of the hardest problems on the team: extending the B2B data graph into the long tail, resolving entity identity at scale, and reading buying intent from meaning rather than keywords. ## Responsibilities - Extend ZoomInfo's data graph into the long tail of companies with little public footprint, extracting leadership, locations, and products from company websites and detecting stale records. - Predict what the graph doesn't know yet, estimating headcount and revenue for under-documented companies using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. - Determine whether two records describe the same company or person, measuring both wrongly merged and wrongly split outcomes. - Infer buying intent from the meaning of web content across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. - Build agents that research companies and cite sources, and design the evaluations that separate a correct result from a run that merely finished. - Distill large models into smaller ones that run cost-effectively across the full dataset, owning quantization and serving as part of the same work. - Take ambiguous, high-stakes problems from undefined to shipped, setting technical direction and raising the engineering bar through design review and mentorship. ## Requirements - You have taken machine learning systems to production and owned them after launch, with technical leadership as an individual contributor , setting direction for a problem area, leading design review, and mentoring; depth matters more than years. - You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. - You have deployed language processing at scale , text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. - You have built and operated LLM agents or multi-step systems in production, including tool and context design, failure analysis from traces, and evaluation for systems with no single right answer, using LLM judges validated against human labels. - You are proficient in production Python and strong SQL with distributed data processing experience, and you use AI coding tools daily with rigorous review of their output. ## Benefits We offer comprehensive benefits, holistic mind, body and lifestyle programs designed for overall well-being. ## Salary $192,500-$302,500 USD ## Skills ### Required - machine learning - classical machine learning - supervised learning - feature engineering - applied statistics - language processing - text classification - information extraction - entity linking - Python - SQL - distributed data processing ### Nice to have - ranking and retrieval - embeddings - learned re-ranking - propensity modeling - clustering - entity resolution - PyTorch - LLM systems --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/zoominfo/jobs/8628076002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)