Staff Software Engineer, Machine Learning, YouTube Shopping Recommendations
Google Inc., Mountain View, CA, United States
Staff Software Engineer, Machine Learning, YouTube Shopping Recommendations
Location: Mountain View, CA, USA
Advanced
Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
Qualifications
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience building and deploying recommendation systems models in production, and building architecture in modeling domains.
5 years of experience with machine learning (ML) design and infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Experience with C++ or Python.
Preferred qualifications
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
Experience designing, building, and operating large-scale interactive systems (e.g., search, ads, or recommender platforms).
Experience using ML frameworks such as TensorFlow or Jax.
Ability to communicate technical concepts to audiences and driving collaboration.
Responsibilities
Guide the development of personalized recommendations that shape the YouTube Shopping experience for millions of users.
Serve as a technical leader, responsible for defining the team's charter, identifying new product opportunities, and executing projects that bridge gaps in the recommendations ecosystem.
Drive viewer growth by designing and implementing machine learning (ML) technologies and algorithms to enhance Shopping recommendation quality across YouTube surfaces, including Home, Watch Next, and Shorts.
Drive cross-team and cross-functional collaborations, working with the product manager for YouTube Shopping recommendations and cross-functional partners to build a team for billions of users.
Gain experience across the recommendation system stack, working with and developing technologies such as model architecture and large language models (LLMs).
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.
The YouTube Shopping Viewer team is at the forefront of a systemic shift in how viewers interact with content. Our mission is to fundamentally change video commerce by building a seamless shopping experience directly into the platform. We’re partnering with some of the world's largest retailers and store builders to natively integrate products into videos. When viewers engage with these products, creators earn commission, allowing them to monetize their content with minimal effort while helping their audience discover and decide what to buy.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
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.
English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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Location: Mountain View, CA, USA
Advanced
Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
Qualifications
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience building and deploying recommendation systems models in production, and building architecture in modeling domains.
5 years of experience with machine learning (ML) design and infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Experience with C++ or Python.
Preferred qualifications
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
Experience designing, building, and operating large-scale interactive systems (e.g., search, ads, or recommender platforms).
Experience using ML frameworks such as TensorFlow or Jax.
Ability to communicate technical concepts to audiences and driving collaboration.
Responsibilities
Guide the development of personalized recommendations that shape the YouTube Shopping experience for millions of users.
Serve as a technical leader, responsible for defining the team's charter, identifying new product opportunities, and executing projects that bridge gaps in the recommendations ecosystem.
Drive viewer growth by designing and implementing machine learning (ML) technologies and algorithms to enhance Shopping recommendation quality across YouTube surfaces, including Home, Watch Next, and Shorts.
Drive cross-team and cross-functional collaborations, working with the product manager for YouTube Shopping recommendations and cross-functional partners to build a team for billions of users.
Gain experience across the recommendation system stack, working with and developing technologies such as model architecture and large language models (LLMs).
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.
The YouTube Shopping Viewer team is at the forefront of a systemic shift in how viewers interact with content. Our mission is to fundamentally change video commerce by building a seamless shopping experience directly into the platform. We’re partnering with some of the world's largest retailers and store builders to natively integrate products into videos. When viewers engage with these products, creators earn commission, allowing them to monetize their content with minimal effort while helping their audience discover and decide what to buy.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
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.
English proficiency is a requirement for all roles unless stated otherwise in the job posting.
#J-18808-Ljbffr