Sr Staff Machine Learning Engineer Jobs in Mountain View, CA
Sr Staff Machine Learning Engineer jobs in Mountain View are concentrated in the North Bayshore and Middlefield Road corridors, with strong demand across AI infrastructure, autonomous systems, and cloud platforms. Employers hiring right now include Google, ServiceNow, and Intuit. See the openings below and apply to the ones that match your experience.
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Showing 5 of 146+ Sr Staff Machine Learning Engineer jobs
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development, including 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience in building ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
- Experience integrating generative AI tools or LLM interfaces into workflows.
- Experience in data processing software (e.g., Hadoop, Spark, Beam, Hive), strategies (e.g., ETL, ELT, CDC) or algorithms (e.g., MapReduce, Flume).
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.
- 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
- Experience in full-stack development, building back-end distributed infrastructure, and programming in Java, Python, or C++.
- Experience integrating generative AI tools and understanding of AI architecture.
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.
The Search Ecosystem team builds a sustainable content ecosystem for Google products. We develop scalable platforms to address Google's content requirements by systematically identifying knowledge gaps in our AI models, sourcing high-quality content to fill them, and then training the models to verify performance improvements. This is a high-impact, high-visibility growth area within Search Ecosystems.
This is an opportunity to work on a business-critical product that is redefining the boundaries of artificial intelligence. We are a fast-moving, growing organization working on highly impactful projects. In this role, you will help build robust systems and scalable platforms that power content acquisition to train AI models in a responsible and secure manner.
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.
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.
Responsibilities
- Develop and implement frameworks and methodologies for evaluating the quality and effectiveness of AI system components and data.
- Analyze evaluation results to drive improvements in system performance and underlying value models.
- Play a key role in building and articulating the high-level technical strategy for your area of ownership.
- Leverage knowledge of LLMs to design, build, and maintain specialized infrastructure on top of LLMs
- Drive technical projects from ideation through to production, working effectively in an ambiguous and fast-paced environment.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development, including 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience in building ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
- Experience integrating generative AI tools or LLM interfaces into workflows.
- Experience in data processing software (e.g., Hadoop, Spark, Beam, Hive), strategies (e.g., ETL, ELT, CDC) or algorithms (e.g., MapReduce, Flume).
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.
- 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
- Experience in full-stack development, building back-end distributed infrastructure, and programming in Java, Python, or C++.
- Experience integrating generative AI tools and understanding of AI architecture.
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.
The Search Ecosystem team builds a sustainable content ecosystem for Google products. We develop scalable platforms to address Google's content requirements by systematically identifying knowledge gaps in our AI models, sourcing high-quality content to fill them, and then training the models to verify performance improvements. This is a high-impact, high-visibility growth area within Search Ecosystems.
This is an opportunity to work on a business-critical product that is redefining the boundaries of artificial intelligence. We are a fast-moving, growing organization working on highly impactful projects. In this role, you will help build robust systems and scalable platforms that power content acquisition to train AI models in a responsible and secure manner.
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.
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.
Responsibilities
- Develop and implement frameworks and methodologies for evaluating the quality and effectiveness of AI system components and data.
- Analyze evaluation results to drive improvements in system performance and underlying value models.
- Play a key role in building and articulating the high-level technical strategy for your area of ownership.
- Leverage knowledge of LLMs to design, build, and maintain specialized infrastructure on top of LLMs
- Drive technical projects from ideation through to production, working effectively in an ambiguous and fast-paced environment.
See All 146+ Sr Staff Machine Learning Engineer Jobs in Mountain View
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Find JobsSr Staff Machine Learning Engineer Job Market in Mountain View
Who's Hiring
- Google54
- ServiceNow43
- Intuit11
- Coupang11
- Waymo5
Top Industries Hiring
- Retail
- Technology & Software
Sr Staff Machine Learning Engineer Jobs in Mountain View: Frequently Asked Questions
How do I get a sr staff machine learning engineer job in Mountain View?
The strongest path into Mountain View's sr staff ML market is through its dense cluster of AI-first product companies and large platform teams in North Bayshore and the Castro Street area. Candidates who combine distributed systems depth with hands-on LLM or recommendation-system work stand out. Contributing to open-source ML tooling and building a portfolio of shipped production models accelerates hiring conversations with Mountain View's research-heavy employer base.
Which companies hire sr staff machine learning engineers in Mountain View?
Employers hiring sr staff machine learning engineers in Mountain View right now include Google, ServiceNow, and Intuit, based on current listings on Migrate Mate as of November 2026. Mountain View draws a mix of large platform companies with dedicated ML infrastructure teams and mid-stage AI startups scaling their core modeling work.
Are there remote sr staff machine learning engineer jobs in Mountain View?
Yes, though sr staff machine learning engineer roles skew toward hybrid given the collaboration-intensive nature of model development and cross-functional reviews. About 31% of sr staff machine learning engineer openings tied to Mountain View are remote or hybrid as of November 2026, with fully remote arrangements most common for roles focused on offline experimentation, research, and model evaluation rather than production deployment work.
How can I get a sr staff machine learning engineer job in Mountain View with little or no experience?
The most realistic entry path locally is through Mountain View's large platform companies, which hire associate or mid-level ML engineers into rotation programs and then promote from within. Targeting roles on data engineering or ML platform teams at these employers builds the production-system familiarity the sr staff level requires. Participating in Mountain View-area AI meetups and Google-adjacent open-source projects also puts candidates in front of the hiring managers who fill these roles.
Which industries hire the most sr staff machine learning engineers in Mountain View?
The sectors hiring the most sr staff machine learning engineers in Mountain View are Retail and Technology & Software, based on current listings on Migrate Mate as of November 2026. Mountain View's role as headquarters for several global platform companies means demand is anchored in product-scale ML rather than research-only or consulting work.
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See All 146+ Sr Staff Machine Learning Engineer Jobs in Mountain View
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