[Hiring] Director, Applied AI @ZoomInfo Technologies LLC

Role Description

You'll lead the team that builds the intelligence every ZoomInfo AI agent reasons over — what's true about companies and the people in them, how they relate, and what they're buying. This role owns the B2B data graph strategy end to end, from training data through model serving, blending classical machine learning and data science with LLM and agentic systems. You'll set the technical bar for a small, senior team while staying hands-on, shipping code and prototypes alongside the engineers you lead.

What You'll Do

• Extend ZoomInfo's B2B data graph into the long tail, making it the most comprehensive and accurate resource available, including companies with little public footprint.
• Lead the team's work on agent memory, distinguishing what a user has supplied from what a system of record already owns.
• Choose the right method for each problem — classical machine learning, language models, or code — based on measured evidence, and stop work that won't pay off.
• Define the evaluation bar for the team's models and agents, building evaluation datasets, regression gates, and experiment designs that make quality claims trustworthy.
• Own inference cost, latency, and capacity as core disciplines alongside model quality, including build-versus-buy and distillation decisions.
• Hire and develop machine learning engineers, data scientists, and research engineers, growing senior engineers into technical leaders.
• Represent the team's work across product, platform, security, and legal, and present results and their limits clearly to executives.
• Set the standard for how the team uses agentic coding tools, pairing precise specifications with rigorous code review.

Qualifications

• Significant, demonstrated experience building and shipping production machine learning systems.
• Track record of hiring and developing senior machine learning engineers and data scientists against a high bar.
• Hands-on experience: shipping code, prototyping independently, and using agentic coding tools daily with rigorous review.
• Deep classical machine learning and data science expertise (supervised learning, feature engineering, statistical inference, experiment design, strong SQL).
• Experience with production LLM and agentic systems, including setting evaluation standards such as leakage-safe validation and calibration.
• Owned inference cost, latency, and capacity alongside model quality, including build-versus-buy decisions.
• Ability to communicate results and their limits clearly to executive stakeholders.

Requirements

• Entrepreneurial experience — founding a company, or taking a product from inception to paying customers as a founding or early engineer.
• Experience in propensity modeling, ranking and retrieval, clustering, or entity resolution at scale.
• Worked on web-scale language processing over multilingual, noisy text, knowledge graphs, or user memory for agents.
• Experience with post-training and distillation, open-weight model serving, or AI governance and safety practices (ISO/IEC 42001, NIST AI RMF).

Benefits

• Comprehensive benefits including holistic mind, body, and lifestyle programs designed for overall well-being.
• Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training.
• US base salary for this position ranges from $233,100 to $366,300 USD.