Machine Learning Engineer III

At Zoom Info, we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. We value your take charge, take initiative, get stuff done attitude and will help you unlock your growth potential. One great choice can change everything. Thrive with us at Zoom Info.

At Zoom Info, we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. We value your take charge, take initiative, get stuff done attitude and will help you unlock your growth potential. One great choice can change everything. Thrive with us at Zoom Info.

Zoom Info 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.

The Applied AI team builds the intelligence layer that sits between Zoom Info'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 Zoom Info'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 (*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

Named Entity Recognition & Data Extraction

• 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

Agentic Workflows & Evaluation

• 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

Scalable Production Systems

• 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 Zoom Info'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

Cross-Functional Collaboration & Prototyping

• 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

What 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 technologies
• Experience with named entity recognition, summarization and data extraction at scale is a plus

Technical Skills

• Proficiency in PyTorch or Tensor Flow for model development and fine-tuning
• Experience with vector databases (Pinecone, Weaviate, FAISS, Open Search) and hybrid retrieval systems
• Strong software engineering skills in Python; familiarity with Go/Java is a plus
• Knowledge of MLOps tools:
  Docker, Kubernetes, Git Ops, 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…