Machine Learning Engineer, ZoomInfo

• 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 technologies
• Experience with named entity recognition, summarization and data extraction at scale is a plus
• Proficiency in PyTorch or TensorFlow for model development and fine-tuning
• Experience with vector databases (Pinecone, Weaviate, FAISS, OpenSearch) and hybrid retrieval systems
• Strong software engineering skills in Python; familiarity with Go/Java is a plus
• Knowledge of MLOps tools: Docker, Kubernetes, GitOps, feature stores, model registries
• Applied AI Expertise
• Hands-on experience with LLM fine-tuning techniques (LoRA, quantization, distillation) is a plus
• Understanding of agentic workflows and multi-agent systems
• Experience building language-agnostic ML solutions and cross-lingual models
• Knowledge of entity resolution and knowledge graph concepts
• Collaboration & Communication
• Ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders
• Experience mentoring junior team members and contributing to team knowledge sharing
• Strong problem-solving skills and ability to work independently with guidance from team leads

Desirable

• 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
• Build and fine-tune embedding models using large language models (Llama) and small language models (*BERT*) for various text understanding tasks
• Develop language-agnostic clustering and classification models using vector search technologies
• Optimize embedding models for production deployment at petabyte scale
• Build high-recall NER models to extract people, organizations, locations, and industry-specific entities from web-extracted data
• Develop robust data extraction pipelines that process diverse web content and structure unstructured information
• Design and implement agentic workflows focused on web extraction, NER, and entity resolution
• Create comprehensive evaluation frameworks for agent performance and reliability
• Collaborate on agent optimization and performance tuning
• Deploy and maintain ML models serving millions of users daily with sub-second latency requirements
• Work with engineering teams to ensure models integrate seamlessly into ZoomInfo's platform architecture
• Monitor model performance and implement automated retraining pipelines to design cost-aware training & inference workflows
• Use integrated CI/CD and testing workflows for seamless deployment
• Partner with product managers and engineering teams to translate business requirements into ML solutions
• Prototype and benchmark emerging AI/infra tech
• Present findings and technical solutions to stakeholders across the organization