Software Engineering Manager, YouTube Ads Machine Learning

Google LLC; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google seeks an experienced Software Engineering Manager for YouTube Ads Machine Learning in Mountain View, CA. You will lead ML system design, model deployment, and research for ad recommendations, while steering teams toward ambitious technical goals.

Requirements include a strong Java/C++-style software foundation, 8+ years in software development, and 2+ years in people management, plus GenAI/domain expertise. In-person interviews are typical.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years leading ML design and optimizing ML infrastructure.
• 3 years in a technical leadership role.
• 2 years with GenAI techniques or related concepts.
• 2 years in people management or team leadership.

Responsibilities

• Set and communicate team priorities aligned to organizational goals.
• Define expectations and provide feedback and coaching regularly.
• Develop mid-term technical goals and roadmaps for multiple teams.
• Build end-to-end ML systems on large-scale data and research new models.
• Collect ground truth, run experiments, tune metrics, and iterate.

Skills

Software development experience

ML design leadership

GenAI techniques

Technical leadership

People management

Education

Bachelor's degree or equivalent

Master’s or PhD in Engineering/CS (preferred)

Job description

Software Engineering Manager, YouTube Ads Machine Learning

Share Software Engineering Manager, YouTube Ads Machine Learning

corporate_fare YouTube place Mountain View, CA, USA

info_outline X In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 2 years of experience in a people management or team leadership role.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization.
• Strong problem solving and quantitative reasoning skills, demonstrated in a mathematical field such as data science, optimization, machine learning, or natural science.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your extensive technical expertise you take initiative to independently design and implement new systems, designing, implementing, and testing multiple features with little or no direction from tech lead or manager. You collaborate with key stakeholders to determine future direction of work.

The YouTube Ads ML team is a research focused product team where we apply machine learning techniques for making ad recommendations on YouTube.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your extensive technical expertise you take initiative to independently design and implement new systems, designing, implementing, and testing multiple features with little or no direction from tech lead or manager. You collaborate with key stakeholders to determine future direction of work.

The YouTube Ads ML team is a research focused product team where we apply machine learning techniques for making ad recommendations on YouTube.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

• Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
• Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
• Develop the mid-term technical goals and roadmap within the scope of your (often multiple) team(s). Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
• Build end to end machine learning systems on large scale data and research novel deep model architectures, read papers, implement and deploy them.
• Collect ground truth, exploratory models, feature engineering, deep model architectures, live experiments on YouTube users, tuning, metrics analysis.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.