Machine Learning Manager Jobs in Mountain View, CA
Machine Learning Manager jobs in Mountain View are concentrated in the North Bayshore corridor, Castro Street district, and the Middlefield Road tech cluster, with strong demand from the AI, cloud infrastructure, and consumer technology sectors. Employers actively hiring include ServiceNow, Unity Technologies, and Intuit. See the openings below and apply to the ones that match your experience.
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Showing 5 of 714+ Machine Learning Manager jobs
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- 8 years of experience with data structures and algorithms.
- 6 years of ML or Quality experience working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, deep model.
- Experience in C++, Dremel/F1 and TensorFlow.
- Experience working with research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
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 technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
As a part of the Discover Personalization team, you will help people feel positively connected and informed about the world around them by delivering the pulse of the Internet that matters to you, within Google Search. You will contribute to the key product's appeal, which lies in having an understanding of users and will be laser focused on building foundational user models for users using all of their interactions across Google products, and leveraging them to power Discover’s retrieval and ranking. You will manage some of the toughest ML and Quality problems, including Neural Deep Retrieval, Activity Clustering, Reinforcement Learning and Multi-Objective Ranking.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design and implement personalized user models to optimize for user happiness, including Neural Deep Retrieval Models, Deep Neural Network Ranking/Scoring models, User/Content Clustering Models, Large Language Models (LLM)-based Retrieval Augmented Generation Models, and more.
- Build user and content clustering models to enable core personalization and ranking use cases.
- Enhance model performance and personalization precision/recall through advanced modeling techniques such as transformers, distillation, reward shaping, multi-task learning, neural bandits, etc. and capabilities through feature engineering, automatic parameter tuning, label quality engineering, etc.
- Scale the model's applications to a multitude of modalities (content, queries, videos and notifications) and use cases (retrieval, ranking, content generation, diversification, etc.).
- Create next-generation realtime ML models that can capture new user interests and world trends in seconds and scale model training and serving to billions of users.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- 8 years of experience with data structures and algorithms.
- 6 years of ML or Quality experience working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, deep model.
- Experience in C++, Dremel/F1 and TensorFlow.
- Experience working with research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
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 technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
As a part of the Discover Personalization team, you will help people feel positively connected and informed about the world around them by delivering the pulse of the Internet that matters to you, within Google Search. You will contribute to the key product's appeal, which lies in having an understanding of users and will be laser focused on building foundational user models for users using all of their interactions across Google products, and leveraging them to power Discover’s retrieval and ranking. You will manage some of the toughest ML and Quality problems, including Neural Deep Retrieval, Activity Clustering, Reinforcement Learning and Multi-Objective Ranking.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design and implement personalized user models to optimize for user happiness, including Neural Deep Retrieval Models, Deep Neural Network Ranking/Scoring models, User/Content Clustering Models, Large Language Models (LLM)-based Retrieval Augmented Generation Models, and more.
- Build user and content clustering models to enable core personalization and ranking use cases.
- Enhance model performance and personalization precision/recall through advanced modeling techniques such as transformers, distillation, reward shaping, multi-task learning, neural bandits, etc. and capabilities through feature engineering, automatic parameter tuning, label quality engineering, etc.
- Scale the model's applications to a multitude of modalities (content, queries, videos and notifications) and use cases (retrieval, ranking, content generation, diversification, etc.).
- Create next-generation realtime ML models that can capture new user interests and world trends in seconds and scale model training and serving to billions of users.
See All 714+ Machine Learning Manager Jobs in Mountain View
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Find Machine Learning Manager JobsMachine Learning Manager Job Market in Mountain View
Who's Hiring
- ServiceNow171
- Unity Technologies93
- Intuit78
- Google62
- Nuro47
Top Industries Hiring
- Technology & Software109
- Retail16
- Automotive16
- Electronics & Hardware16
- Artificial Intelligence16
Machine Learning Manager Jobs in Mountain View: Frequently Asked Questions
How do I get a machine learning manager job in Mountain View?
The strongest path into a machine learning manager role in Mountain View runs through the city's dense concentration of AI-first companies and large tech campuses along North Bayshore and Middlefield Road. Candidates who stand out typically combine hands-on ML engineering experience with demonstrated team leadership, ideally on deployed production systems. Familiarity with the infrastructure and scale challenges common at Mountain View's cloud and consumer-tech employers gives applicants a clear edge over generalist candidates.
Which companies hire machine learning managers in Mountain View?
Mountain View machine learning manager roles are posted by ServiceNow, Unity Technologies, and Intuit and others right now, based on current listings on Migrate Mate as of November 2026. The local employer base skews heavily toward established technology companies with large-scale AI and data platform teams, alongside a growing number of well-funded AI startups that have chosen Mountain View for its proximity to research talent.
Are there remote machine learning manager jobs in Mountain View?
Yes, though remote availability varies since machine learning manager roles often involve close collaboration with engineering teams and hands-on model review that benefits from in-person presence. About 36% of machine learning manager openings tied to Mountain View are remote or hybrid as of November 2026, with the most flexibility typically found in strategy and research-oriented roles rather than those directly embedded in product engineering pods.
How can I get a machine learning manager job in Mountain View with little or no experience?
The most realistic entry path in Mountain View is moving up from a senior ML engineer role within one of the city's large tech employers, where internal promotions into team lead and manager positions are common. Smaller AI startups along Stierlin Court and the North Bayshore area also tend to create first-time manager opportunities faster than enterprise organizations. Building a visible record of mentoring engineers, driving cross-functional ML projects, and contributing to open-source model work strengthens a transition into management at Mountain View employers.
Which industries hire the most machine learning managers in Mountain View?
Most machine learning manager openings in Mountain View sit in Technology & Software, Retail, and Automotive, per current listings on Migrate Mate as of November 2026. Mountain View's identity as a headquarters city for major internet and cloud platforms means those sectors consistently generate the highest volume of ML leadership roles, with demand reinforced by the city's proximity to Stanford research pipelines and a deep local pool of specialized engineering talent.
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See All 714+ Machine Learning Manager Jobs in Mountain View
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