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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 set the technical direction for the intelligence layer every ZoomInfo AI agent reasons over — what's true about companies and the people in them, how they relate, and what they're buying. As a senior individual contributor with no direct reports, you will own strategy across the data graph, entity resolution, and buying intent, staying hands-on in the hardest of these problems. You'll decide when classical machine learning, statistics, or language models is the right tool, and turn good judgment into standards other teams adopt. What You'll Do You will set technical strategy for the data graph, entity resolution, buying intent, and agent context, deciding which problems to take on, in what order, and how the pieces connect. You will frame and ship problems nobody has framed yet, such as extraction for companies with no public footprint or semantic intent at web scale, deciding what not to build as deliberately as what to build. You will define evaluation standards that other teams adopt, including sampling methodology, human labels, validated LLM judges, and release gates, and know where each one breaks. You will define the data contracts between the data graph, intent signals, and the agents that consume them, including agent memory, keeping the system cost-effective to run across the full dataset. You will turn good choices into defaults across the group: the baseline every model must beat, how uncertainty is reported, and which metrics get retired when they mislead. You will lead design reviews, mentor senior engineers, shape hiring, and represent the team's technical judgment to product and leadership. What You Bring Must-Have: You have set technical direction as an individual contributor for a problem area spanning more than one team, with the resulting machine learning systems in production and owned after launch — depth of impact matters more than years or past titles. You bring breadth across classical machine learning on large, messy tabular data, applied statistics, language processing at scale, and LLM agents or multi-step systems, with recognized depth in at least one. You have defined and driven adoption of evaluation standards beyond your own team for systems with no single right answer, including LLM judges validated against human labels and results reported with their limits. You have a track record of changing how a group builds or measures — for example, introducing a baseline or review practice that other teams now use. You have made cost and capacity decisions for model training and serving, including when to self-host, distill, or call a hosted model, with cost tracked per unit of work. You are hands-on in production Python and strong SQL with distributed data processing experience, and you use AI coding tools daily with rigorous review of their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring entity resolution, knowledge graph, or web-scale information extraction experience on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, including GPU capacity planning. You have built user memory or context systems for agents, or defended LLM systems against adversarial inputs and prompt injection. #LI-Remote #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. $192,500 — $302,500 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. 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.

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 help build 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. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch. What You'll Do You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document. You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. You will determine whether two records describe the same company or person, measuring both false merges and false splits. You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates. You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving. You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review. What You Bring Must-Have: You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years. You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels. You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work. You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents. #LI-Remote #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. $128,100 — $201,300 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. 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.

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 help build 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. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch. What You'll Do You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document. You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. You will determine whether two records describe the same company or person, measuring both false merges and false splits. You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates. You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving. You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review. What You Bring Must-Have: You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years. You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels. You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work. You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents. #LI-Remote #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. $128,100 — $201,300 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. 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.

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 help build 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. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch. What You'll Do You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document. You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. You will determine whether two records describe the same company or person, measuring both false merges and false splits. You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates. You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving. You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review. What You Bring Must-Have: You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years. You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels. You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work. You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents. #LI-Remote #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. $128,100 — $201,300 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. 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.

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 help build 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. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch. What You'll Do You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document. You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. You will determine whether two records describe the same company or person, measuring both false merges and false splits. You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates. You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving. You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review. What You Bring Must-Have: You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years. You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels. You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work. You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents. #LI-Remote #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. $128,100 — $201,300 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. 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.

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 help build 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. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch. What You'll Do You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document. You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. You will determine whether two records describe the same company or person, measuring both false merges and false splits. You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates. You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving. You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review. What You Bring Must-Have: You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years. You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels. You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work. You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents. #LI-Remote #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. $128,100 — $201,300 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. 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.

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 help build 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. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch. What You'll Do You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document. You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty. You will determine whether two records describe the same company or person, measuring both false merges and false splits. You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations. You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates. You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving. You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review. What You Bring Must-Have: You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years. You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance. You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text. You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels. You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output. Preferred: You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG. You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data. You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work. You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents. #LI-Remote #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. $128,100 — $201,300 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. 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.

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. As a Senior Software Engineer on the Integrations team, you'll design and build the systems that connect ZoomInfo's platform to the ecosystem of CRM, MAP, and external eco-systems that our customers depend on. You'll work on highly scalable backend services that power reliable, real-time data sync and API integrations across millions of records — enabling seamless connectivity between ZoomInfo and platforms like Salesforce, HubSpot, and Microsoft Dynamics 365. You'll leverage technologies like Kafka, Confluent Cloud, Node.js/NestJS, and modern API and authentication standards to build resilient, observable, and fault-tolerant integration services. Your work will be foundational to how ZoomInfo's data reaches customers and connects with the tools at the center of their go-to-market stack. Our engineering culture values diversity, intellectual curiosity, problem-solving, and openness. We encourage collaboration, big thinking, and calculated risk-taking in a blame-free environment. You'll have the autonomy to work on meaningful projects while receiving the support and mentorship needed to grow your career. What You'll Do: Own the platform integrations layer end-to-end — building reliable connectivity, data ingestion/exports, and orchestration for complex, multi-step, long-running processes (including retries and state management) Build and maintain both inbound and outbound integrations with third-party platforms (e.g., Salesforce and other external/open APIs) Design and implement in-house services capable of processing large volumes of data under tight time constraints, optimizing for throughput and latency Design and maintain RESTful and webhook-based APIs, applying strong patterns for rate limiting, pagination, error handling, versioning, and backward compatibility Collaborate with product and platform teams to define integration requirements and execution guarantees (SLAs/SLOs) Build observability (logging, tracing, metrics) into integration systems, and use it to monitor, troubleshoot, and continuously improve production reliability Lead medium/large feature development independently within agile processes, mentoring engineers and conducting code reviews along the way Stay current with emerging technologies and evaluate new tools for potential adoption What You Bring: 5+ years of software engineering experience with a focus on backend systems Strong experience with Node.js (NestJS), JavaScript, and TypeScript; Java (Spring Boot) is a plus Proven experience integrating with external/third-party APIs, building both inbound and outbound integrations (any platform — pattern/concept experience is transferable) Demonstrated experience building high-volume data services — e.g., optimizing data processing/ingestion time under real-world constraints Strong problem-solving and analytical skills, with the ability to debug complex technical issues and implement robust solutions Solid understanding of authentication and authorization protocols, including OAuth 2.0, OIDC, SAML, and JWT Proficiency with MongoDB and comfort working across relational and NoSQL data stores; familiarity with React a plus Strong communicator, comfortable leading cross-functional collaboration with both technical and non-technical stakeholders #LI-LM1 #LI-Remote 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. $140,000 — $220,000 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. 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.