Director, Applied AI
ZoomInfo · Waltham, Massachusetts, United States
About this role
**ZoomInfo — Director, Applied AI** ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life—surrounded by teammates who care deeply, challenge each other, and celebrate wins. ## What you’ll do - Lead the team that builds the intelligence ZoomInfo AI agents reason over: what’s true about companies and the people in them, how they relate, and what they’re buying. - Own 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. - Extend ZoomInfo’s B2B data graph into the long tail to make it the most comprehensive and accurate resource, including companies with little public footprint. - Lead work on agent memory, distinguishing what a user has supplied vs. what a system of record already owns. - Choose the right approach for each problem (classical ML, language models, or code) using measured evidence, and stop work that won’t pay off. - Define evaluation standards: build evaluation datasets, regression gates, and experiment designs that make quality claims trustworthy. - Own inference cost, latency, and capacity alongside model quality, including build-vs-buy and distillation decisions. - Hire and develop machine learning engineers, data scientists, and research engineers; grow senior engineers into technical leaders. - Represent the team across product, platform, security, and legal; present results and limitations clearly to executives. - Set the standard for how the team uses agentic coding tools with precise specs and rigorous code review. ## What you bring **Must-Have** - Significant experience building and shipping production ML systems; lead by building alongside your team. - Track record hiring and developing senior ML engineers and data scientists at a high bar. - Stay hands-on: ship code, prototype independently, and use agentic coding tools daily with rigorous review. - Deep classical ML/data science expertise (supervised learning, feature engineering, statistical inference, experiment design, strong SQL) plus production LLM/agentic systems—judgment to choose between them and set evaluation standards (e.g., leakage-safe validation, calibration). - Ownership of inference cost, latency, and capacity alongside model quality; communicate results and limitations clearly to executive stakeholders. **Preferred** - Entrepreneurial experience (founding a company or taking a product from inception to paying customers as a founding/early engineer). - Experience with propensity modeling, ranking/retrieval, clustering, or entity resolution at scale. - Experience with web-scale language processing over multilingual/noisy text, knowledge graphs, or agent user memory. - Experience with post-training/distillation, open-weight model serving, or AI governance/safety practices (ISO/IEC 42001, NIST AI RMF). ## Location / Tags - #LI-Remote - #LI-VC1 ## Compensation (US base salary) - **$233,100 — $366,300 USD** Actual compensation depends on factors such as work location, qualifications, skills, experience, and/or training. Additional compensation (bonus, commission, equity, and other benefits) may apply. ## About ZoomInfo ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that helps businesses grow faster with AI-ready insights, trusted data, and advanced automation. ZoomInfo is an equal opportunity employer and hires based on qualifications, merit, and business ne
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