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.
About ZoomInfo
ZoomInfo is building the next generation go-to-market platform using high-quality GTM data, agentic workflows, and a robust intelligence layer to give sales, marketing, and revenue operations teams a competitive advantage.
About the Applied AI Team
The Applied AI team builds the intelligence layer that sits between ZoomInfo's high-quality data and the application layer through which customers engage. Using a product-led growth model, this team leverages customer engagement as input to build better recommendations, scoring, classification, and generative models.
What you will do :
Foundation Data Quality Enhancement
- Improve data quality for ZoomInfo's foundation datasets including firmographics, demographics, C-suite profiles, workforce information, titles, skill sets, scoops, intent signals, and web-extracted data
- Design and implement data validation pipelines and quality metrics to ensure high-fidelity information across millions of records
Embedding and Model Development
Build and fine-tune embedding models using large language models (Llama) and small language models (BERTfor various text understanding tasksDevelop language-agnostic clustering and classification models using vector search technologiesOptimize embedding models for production deployment at petabyte scaleNamed Entity Recognition & Data Extraction
Build high-recall NER models to extract people, organizations, locations, and industry-specific entities from web-extracted dataDevelop robust data extraction pipelines that process diverse web content and structure unstructured informationAgentic Workflows & Evaluation
Design and implement agentic workflows focused on web extraction, NER, and entity resolutionCreate comprehensive evaluation frameworks for agent performance and reliabilityCollaborate on agent optimization and performance tuningScalable Production Systems
Deploy and maintain ML models serving millions of users daily with sub-second latency requirementsWork with engineering teams to ensure models integrate seamlessly into ZoomInfo's platform architectureMonitor model performance and implement automated retraining pipelines to design cost-aware training & inference workflowsUse integrated CI / CD and testing workflows for seamless deploymentCross-Functional Collaboration & Prototyping
Partner with product managers and engineering teams to translate business requirements into ML solutionsPrototype and benchmark emerging AI / infra techPresent findings and technical solutions to stakeholders across the organizationWhat you bring :
Experience & Education
3 - 5 years (1+ years post-PhD) of hands-on ML / NLP experience with demonstrated impact on production systems. Preference for masters and background in Computer Science and other allied data science / engineering disciplines.Strong background in transformer architectures, embedding models, and vector search technologiesExperience with named entity recognition, summarization and data extraction at scale is a plusTechnical Skills
Proficiency in PyTorch or TensorFlow for model development and fine-tuningExperience with vector databases (Pinecone, Weaviate, FAISS, OpenSearch) and hybrid retrieval systemsStrong software engineering skills in Python; familiarity with Go / Java is a plusKnowledge of MLOps tools : Docker, Kubernetes, GitOps, feature stores, model registriesApplied AI Expertise
Hands-on experience with LLM fine-tuning techniques (LoRA, quantization, distillation) is a plusUnderstanding of agentic workflows and multi-agent systemsExperience building language-agnostic ML solutions and cross-lingual modelsKnowledge of entity resolution and knowledge graph conceptsCollaboration & Communication
Ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholdersExperience mentoring junior team members and contributing to team knowledge sharingStrong problem-solving skills and ability to work independently with guidance from team leadsPreferred Qualifications
Experience processing large-scale unstructured dataBackground in information retrieval and search systemsFamiliarity with MLOps concepts, A / B testing and experimental design for ML systemsKnowledge of data quality frameworks and validation methodologiesLI-SK
LI-Hybrid
Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and / or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process. We want our employees and their families to thrive.
In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being.
