ML Engineer Jobs in Mountain View, CA
ML Engineer jobs in Mountain View are concentrated in the Castro Street corridor, the Shoreline West tech campus cluster, and the broader North Bayshore district, with most demand coming from AI research, cloud infrastructure, and autonomous systems employers. ServiceNow, Nuro, and Google are among those actively hiring right now. See the openings below and apply to the ones that match your experience.
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Showing 5 of 1,027+ ML Engineer jobs
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software design and architecture.
- Experience with C, C++, machine learning, and embedded systems.
- Experience with machine learning algorithms.
- Experience with machine learning architecture.
- Experience with machine learning research.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience taking machine learning models from research prototype to production on mobile or embedded devices, and owning them after launch.
- Experience optimizing models for on-device accelerators through quantization, hardware-aware architecture design, or custom kernels.
- Experience building and training models in JAX/TensorFlow.
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 Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.
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
- Design and implement the real-time on-device machine learning foundation that turns raw camera and sensor input into structured signals driving immediate application behavior.
- Drive the optimization of outlook models for NPU, GPU, and DSP execution, including quantization, hardware-aware architecture design, and custom kernel development, in partnership with the Tensor silicon and compiler teams.
- Own models end-to-end, from prototype through deployment on hundreds of millions of devices — training pipelines in JAX and TensorFlow, C++ integration into the camera pipeline, and long-term maintainability.
- Partner with product, UX, software, and hardware teams to define the requirements for next-generation interactive features, and translate roadmap goals into designs achievable within device constraints.
- Establish best practices for machine learning development, deployment, and evaluation. Define how model quality is measured; and contribute to the long-term technology roadmap.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software design and architecture.
- Experience with C, C++, machine learning, and embedded systems.
- Experience with machine learning algorithms.
- Experience with machine learning architecture.
- Experience with machine learning research.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience taking machine learning models from research prototype to production on mobile or embedded devices, and owning them after launch.
- Experience optimizing models for on-device accelerators through quantization, hardware-aware architecture design, or custom kernels.
- Experience building and training models in JAX/TensorFlow.
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 Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.
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
- Design and implement the real-time on-device machine learning foundation that turns raw camera and sensor input into structured signals driving immediate application behavior.
- Drive the optimization of outlook models for NPU, GPU, and DSP execution, including quantization, hardware-aware architecture design, and custom kernel development, in partnership with the Tensor silicon and compiler teams.
- Own models end-to-end, from prototype through deployment on hundreds of millions of devices — training pipelines in JAX and TensorFlow, C++ integration into the camera pipeline, and long-term maintainability.
- Partner with product, UX, software, and hardware teams to define the requirements for next-generation interactive features, and translate roadmap goals into designs achievable within device constraints.
- Establish best practices for machine learning development, deployment, and evaluation. Define how model quality is measured; and contribute to the long-term technology roadmap.
See All 1,027+ ML Engineer Jobs in Mountain View
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Find ML Engineer JobsML Engineer Job Market in Mountain View
Who's Hiring
- ServiceNow165
- Nuro127
- Google114
- General Motors114
- Coupang76
Top Industries Hiring
- Technology & Software203
- Electronics & Hardware127
- Automotive114
- Banking & Financial Services114
- Artificial Intelligence38
ML Engineer Jobs in Mountain View: Frequently Asked Questions
How do I get a ml engineer job in Mountain View?
The strongest path into Mountain View ml engineer roles runs through the city's AI research labs, cloud platform teams, and autonomous vehicle programs, which cluster around North Bayshore and the Shoreline West corridor. Candidates who can show production ML experience, strong Python and PyTorch or TensorFlow skills, and familiarity with large-scale data pipelines stand out most with local employers. Targeting companies with active AI infrastructure teams in Mountain View directly accelerates the search.
Which companies hire ml engineers in Mountain View?
Mountain View ml engineer roles are posted by ServiceNow, Nuro, and Google and others right now, based on current listings on Migrate Mate as of September 2026. Mountain View's employer mix skews heavily toward large technology companies and well-funded AI startups with deep research mandates rather than staffing or consulting firms.
Are there remote ml engineer jobs in Mountain View?
Yes, though the share varies: ml engineer work that involves model training infrastructure, research, and data pipeline development tends to be highly remote-compatible, while roles tied to robotics hardware or on-site GPU clusters typically require in-person work. About 46% of ml engineer openings tied to Mountain View are remote or hybrid as of September 2026, with the most flexibility found in pure software and research-oriented positions at Mountain View's larger tech campuses.
How can I get a ml engineer job in Mountain View with little or no experience?
The most realistic entry path in Mountain View is through associate or junior ML engineer roles at mid-size AI startups in the North Bayshore and Castro Street areas, where smaller teams often hire candidates who show strong personal projects and open-source contributions over years of industry experience. Internship-to-hire pipelines at Mountain View's larger tech companies are another common route. Candidates who can demonstrate end-to-end model deployment, even on self-directed projects, have a clear edge in local interviews.
Which industries hire the most ml engineers in Mountain View?
The sectors hiring the most ml engineers in Mountain View are Technology & Software, Electronics & Hardware, and Automotive, based on current listings on Migrate Mate as of September 2026. Mountain View's position as the headquarters city for several major technology platforms and AI research organizations means those sectors generate a disproportionately large share of local ml engineer demand compared to most other California cities.
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