应用AI总监
Director, Applied AI
ZoomInfo 是职业加速的地方。我们快速行动，大胆思考，并赋能你完成一生中最好的工作。你将与 deeply 关心工作的队友们一起工作，他们彼此挑战，共同庆祝成功。借助能放大你影响力的各种工具和一个支持你抱负的文化，你不仅会做出贡献，还会迅速实现目标。
你将领导构建 ZoomInfo AI 代理所依赖的智能团队——关于公司和其中人员的真实信息、它们之间的关系以及它们正在购买什么。这个职位将从训练数据到模型服务，全程负责 B2B 数据图谱策略，结合传统机器学习和数据科学与 LLM 和代理系统。你将为一个小而资深的团队设定技术标准，同时保持亲力亲为，与你带领的工程师一起编写代码和原型。
**你将负责**
- 你将把 ZoomInfo 的 B2B 数据图谱扩展到长尾部分，使其成为最全面和准确的资源，包括那些公开信息很少的公司。
- 你将领导团队在代理记忆方面的工作，区分用户提供的信息和系统记录已有的信息。
- 你将根据实证选择最适合问题的方法——传统机器学习、语言模型或代码，并停止那些不会带来回报的工作。
- 你将定义团队模型和代理的评估标准，构建评估数据集、回归门控和实验设计，使质量声明值得信赖。
- 你将把推理成本、延迟和容量作为核心领域，与模型质量并重，包括自建与采购以及模型压缩的决策。
- 你将招聘和发展机器学习工程师、数据科学家和研究工程师，培养高级工程师成为技术领导者。
- 你将在产品、平台、安全和法律部门代表团队的工作，并向高管清晰地展示结果及其局限性。
- 你将设定团队使用代理编码工具的标准，将精确的规范与严格的代码审查相结合。
**你将带来的能力**
_必备条件：_
- 你有显著的、经过验证的经验来构建和部署生产级机器学习系统，并通过与团队一起工作来领导——能力比年限更重要。
- 你有在高标准下招聘和发展高级机器学习工程师和数据科学家的记录。
- 你今天仍然保持亲力亲为：编写代码，提交 PR
查看英文原文
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](https://www.zoominfo.com/careers#benefits).
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) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller.
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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.