Director, Applied AI

This is a fully remote position, open to applicants in Maryland, +2 more states.

📋 Description

• Lead the team responsible for developing the intelligence behind ZoomInfo AI agents, which includes the B2B data graph, training data, model deployment, machine learning, data science, LLMs, and agentic systems.

• Expand ZoomInfo's B2B data graph into the long tail to enhance both comprehensiveness and accuracy.

• Oversee initiatives related to agent memory, differentiating user-provided information from system-of-record data.

• Choose classical machine learning, language models, or coding solutions for each challenge based on empirical evidence.

• Establish evaluation criteria for models and agents, which encompasses evaluation datasets, regression gates, and experimental designs.

• Manage inference costs, latency, and capacity, including decisions around build-versus-buy and distillation strategies.

• Recruit and nurture machine learning engineers, data scientists, and research engineers.

• Represent the team's initiatives across product, platform, security, and legal domains, presenting findings and constraints to executives.

• Set benchmarks for utilizing agentic coding tools through detailed specifications and thorough code reviews.

⛳️ Requirements

• Extensive, proven experience in building and deploying production machine learning systems; capability is prioritized over years of experience.

• A strong history of hiring and mentoring senior machine learning engineers and data scientists who meet high standards.

• Current hands-on experience in deploying code, independently prototyping, and utilizing agentic coding tools regularly with a focus on rigorous review.

• In-depth knowledge of classical machine learning and data science, including supervised learning, feature engineering, statistical inference, experimental design, and advanced SQL.

• Experience in production LLM and agentic systems.

• Sound judgment in selecting classical machine learning, language models, or coding solutions based on empirical evidence.

• Proven experience in establishing evaluation standards such as leakage-safe validation and calibration.

• Experience managing inference costs, latency, and capacity while maintaining model quality, including build-versus-buy evaluations.

• Ability to effectively communicate results and their limitations to executive stakeholders.

• Preferred: entrepreneurial background in founding a company or guiding a product from inception to customer acquisition.

• Preferred: experience in propensity modeling, ranking and retrieval, clustering, or large-scale entity resolution.

• Preferred: familiarity with web-scale language processing over multilingual, noisy text, knowledge graphs, or user memory systems for agents.

• Preferred: experience with post-training and distillation, open-weight model serving, or AI governance and safety standards (ISO/IEC 42001, NIST AI RMF).

🏝️ Benefits

• Comprehensive benefits package.

• Holistic programs for mind, body, and lifestyle aimed at promoting overall well-being.

• Additional compensation options such as bonuses, commissions, equity, and other benefits may also be available.