ZoomInfo Technologies LLC

SeniorMachineLearningEngineer

$165–259k Massachusetts, United States Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Machine Learning Engineer at ZoomInfo Technologies LLC. Skills: ML/NLP, AI architectures, transformer stacks, RAG systems, vector-based information retrieval, NER, entity resolution, knowledge-graph integration, PyTorch, TensorFlow, Python. end-to-end owner of critical projects that enhance the quality and reliability of our core datasets. work at the intersection of cutting-edge AI and massive-scale data processing to solve complex entity resolution challenges”

Industry & Context.

Problems you'll solve

solve complex entity resolution challenges; build language-agnostic clustering and classification systems; tag people, orgs, locations, and industry-specific entities; extracting structured insights from web data; dedupe and merge hundreds of millions of fragmented company and person records; creating enriched, unified entities enhanced with knowledge-graph signals

What They're Looking For.

Must Have

6+ years hands-on ML/NLP experience, at least two delivered, revenue-impacting products in production environments, Python, Go/Java

Nice to Have

3+ years post-PhD/Master's, PhD, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified

What You'll Do.

end-to-end owner of critical projects that enhance the quality and reliability of our core datasets

work at the intersection of cutting-edge AI and massive-scale data processing to solve complex entity resolution challenges

and aligned entity-resolution & knowledge-graph initiatives

invent and productionize Transformer/RAG/Graph RAG architectures

prototype and launch hybrid dense/sparse retrieval pipelines on vector DBs

own high-recall NER models

build cross-dataset entity-resolution frameworks

design and implement agentic workflows

drive end-to-end project ownership from problem definition through deployment

collaborate with engineering and product teams to understand business requirements and translate them into scalable ML solutions

How You'll Work.

Team & Collaboration

partnering with ML engineers to ensure production reliability; translating product goals into measurable ML KPIs; influencing roadmap and investment decisions; collaborating closely with engineering and product teams

Communication Scope

Executive communication skills; ability to persuade technical and non-technical audiences through data-driven storytelling; comfortable owning strategy, budget, and cross-functional collaboration

Process & Methodology

end-to-end project ownership

Full Job Description

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast. Join ZoomInfo's mission to build the next-generation go-to-market platform! ZoomInfo is redefining how 40,000+ revenue teams find, engage, and win customers. As a Senior Data Scientist on our Foundation Data team, you'll be the end-to-end owner of critical projects that enhance the quality and reliability of our core datasets. You'll work at the intersection of cutting-edge AI and massive-scale data processing to solve complex entity resolution challenges that directly impact millions of sales and marketing professionals worldwide. You will own core retrieval, NER, and aligned entity-resolution & knowledge-graph initiatives that touch billions of records and serve millions of daily queries. What You'll Do Invent and productionize Transformer/RAG/Graph RAG architectures that surface the right contact, company, or insight while driving quantization, distillation, and SLM fine-tuning (GTE-Qwen, modernBERT) so models stay fast and affordable at petabyte scale Prototype and launch hybrid dense/sparse retrieval pipelines on vector DBs to build language-agnostic clustering and classification systems that power our intelligence layer Own high-recall NER models that tag people, orgs, locations, and industry-specific entities across multi-language text, extracting structured insights from web data to improve our signal detection capabilities Build cross-dataset entity-resolution frameworks that dedupe and merge hundreds of millions of fragmented company and person records with sub-second latency, creating enriched, unified entities enhanced with knowledge-graph signals Design and implement agentic workflows with robust evaluation framewor

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