Machine Learning Intern Jobs in Mountain View, CA
Machine Learning Intern jobs in Mountain View are concentrated in the North Bayshore tech corridor, the Castro Street business district, and the Moffett Field area, with demand driven by semiconductor, AI research, and cloud infrastructure firms. Companies actively hiring right now include ServiceNow, Google, and Unity Technologies. Find a role that fits below and apply directly.
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Showing 5 of 815+ Machine Learning Intern 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 815+ Machine Learning Intern Jobs in Mountain View
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Find Machine Learning Intern JobsMachine Learning Intern Job Market in Mountain View
Who's Hiring
- ServiceNow177
- Google82
- Unity Technologies82
- Nuro54
- Coupang54
Top Industries Hiring
- Technology & Software95
- Electronics & Hardware54
- Automotive41
- Banking & Financial Services41
- Artificial Intelligence27
Machine Learning Intern Jobs in Mountain View: Frequently Asked Questions
How do I get a machine learning intern job in Mountain View?
Focus your search on Mountain View's North Bayshore corridor and the dense cluster of AI and semiconductor employers near Moffett Field, where most openings appear. Candidates with hands-on experience in Python, PyTorch, or TensorFlow and at least one published or deployed model stand out. Targeting mid-size AI startups alongside larger tech firms gives you a realistic path into the market without competing only for the highest-profile roles.
Which companies hire machine learning interns in Mountain View?
Employers hiring machine learning interns in Mountain View right now include ServiceNow, Google, and Unity Technologies, based on current listings on Migrate Mate as of September 2026. Mountain View's employer mix leans heavily toward established technology companies, AI-focused startups, and research-driven organizations with dedicated applied science teams.
Are there remote machine learning intern jobs in Mountain View?
Yes, though remote availability depends on the role: model research and data pipeline work tends to be more flexible, while hardware-adjacent or lab-based ML projects are almost always on-site. About 47% of machine learning intern openings tied to Mountain View are remote or hybrid as of September 2026, which reflects the city's mix of on-campus tech campuses and research facilities. Analytical and software-heavy duties are most likely to allow remote days.
How can I get a machine learning intern job in Mountain View with little or no experience?
The most realistic entry path in Mountain View is through AI and data-science internship pipelines at mid-size startups in the North Bayshore area, which hire interns with strong coursework and personal projects even without prior industry experience. Contributing to open-source ML repositories, completing a Kaggle competition, or building a portfolio project relevant to computer vision or NLP gives local employers something concrete to evaluate. Research assistant roles at nearby academic institutions also serve as a direct bridge into Mountain View's applied ML hiring pipeline.
Which industries hire the most machine learning interns in Mountain View?
Most machine learning intern openings in Mountain View sit in Technology & Software, Electronics & Hardware, and Automotive, per current listings on Migrate Mate as of September 2026. Mountain View's concentration of AI-native companies, autonomous systems developers, and cloud platform teams makes those sectors the primary engine of local intern demand.
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