Job description

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen fast. 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, blending classical machine learning and data science with LLM and agentic systems, and treating evaluation and inference cost as core disciplines. You'll set the technical bar for a team of senior engineers while staying close to the code, shipping alongside the people you lead. What You'll Do You will ship code alongside your team, prototype alone to prove or kill an idea, and review code as a peer, setting how the team uses agentic coding tools with precise specifications and rigorous review. You will own delivery end-to-end, from problem framing through serving and on-call, including long-tail graph coverage and user memory for agents that separates user-supplied context from system-of-record data. You will choose the right method for each problem — classical machine learning, language models, or code — for challenges like sparse-company revenue estimation, entity resolution, and semantic intent modeling, deciding on measured evidence and stopping work that won't pay off. You will define what it takes to claim an agent's output is correct, not just that its run completed, building the evaluation datasets, regression gates, and experiment designs that back those claims. You will own inference cost, latency, and capacity, including build-versus-buy and distillation decisions, since a model too expensive to run everywhere isn't a result. You will hire and grow machine learning engineers, data scientists, and research engineers, developing senior engineers into technical leaders. You will work across product, platform, security, and legal, and present results and their limits to executives, including when a system isn't good enough to launch. What You Bring Must-Have: You have significant experience building production machine learning systems and leading the engineers who build them by shipping alongside them — demonstrated capability matters more than years. You have a track record of hiring and developing senior machine learning engineers and data scientists against a high bar. You stay hands-on today: shipping code, building prototypes independently, and using agentic coding tools daily with rigorous review. You bring deep classical machine learning and data science expertise (supervised learning, feature engineering, statistical inference and experiment design, strong SQL) alongside production LLM and agentic systems, with the judgment to choose between them, including setting an evaluation bar with leakage-safe validation, calibration, and validated LLM judges. You have a record of cost and capacity decisions for model serving, such as moving a workload from a hosted model to a distilled or self-hosted one, with the savings measured, and you report results to executives with their limits stated, including recommending against a launch. Preferred: You bring entrepreneurial experience — founding a company, or taking a product from inception to paying customers as a founding or early engineer. You have experience in propensity modeling, ranking and retrieval, clustering, or entity resolution at scale. You have worked on web-scale language processing over multilingual, noisy text, knowledge graphs, or user memory for agents. You have experience with post-training and distillation, open-weight model serving, or AI governance and safety practices (ISO/IEC 42001, NIST AI RMF). #LI-Hybrid #LI-VC1 Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process. We want our employees and their families to thrive. In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here . Below is the US base salary for this position. Additional compensation such as Bonus, Commission, Equity and other benefits may also apply. $233,100 — $366,300 USD About us: ZoomInfo (NASDAQ: GTM), the all-in-one AI GTM platform, enables sales, marketing, and customer success teams to execute their go-to-market strategy with confidence. Powered by the industry's most comprehensive B2B data, including more than 100 million companies, 500 million contacts, and billions of signals, ZoomInfo delivers the intelligence, automation, and integrations that modern revenue teams need to identify, engage, and convert their best buyers. ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant Privacy Notice for more details on how we handle your personal information. ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available here . ZoomInfo is proud to be an equal opportunity employer, hiring based on qualifications, merit, and business needs, and does not discriminate based on protected status. We welcome all applicants and are committed to providing equal employment opportunities regardless of sex, race, age, color, national origin, sexual orientation, gender identity, marital status, disability status, religion, protected military or veteran status, medical condition, or any other characteristic protected by applicable law. We also consider qualified candidates with criminal histories in accordance with legal requirements. For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. ZoomInfo does not administer lie detector tests to applicants in any location.

Requirements

Must-haves

You will ship code alongside your team, prototype alone to prove or kill an idea, and review code as a peer, setting how the team uses agentic coding tools with precise specifications and rigorous review.
You will own delivery end-to-end, from problem framing through serving and on-call, including long-tail graph coverage and user memory for agents that separates user-supplied context from system-of-record data.
You will define what it takes to claim an agent's output is correct, not just that its run completed, building the evaluation datasets, regression gates, and experiment designs that back those claims.
You will own inference cost, latency, and capacity, including build-versus-buy and distillation decisions, since a model too expensive to run everywhere isn't a result.
You will hire and grow machine learning engineers, data scientists, and research engineers, developing senior engineers into technical leaders.
You will work across product, platform, security, and legal, and present results and their limits to executives, including when a system isn't good enough to launch.
You have significant experience building production machine learning systems and leading the engineers who build them by shipping alongside them — demonstrated capability matters more than years.
You have a track record of hiring and developing senior machine learning engineers and data scientists against a high bar.
You stay hands-on today: shipping code, building prototypes independently, and using agentic coding tools daily with rigorous review.
ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant Privacy Notice for more details on how we handle your personal information.
ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available here .

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningllmsqlgo

Platform: greenhouse
Effort: quick