Machine Learning Intern Jobs in San Jose, CA
Machine Learning Intern jobs in San Jose are concentrated in North San Jose, Downtown San Jose, and the Alviso corridor, with strong demand across semiconductor, enterprise software, and AI infrastructure sectors. Employers actively hiring include TikTok, ByteDance, and Adobe. Scan the live roles below and apply to whichever ones fit.
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About the Role:
The SDC team is dedicated to empowering customers – from creative professionals to everyday users – with intelligent tools to create, manage, and discover digital content. We are building the next-generation platform stack to support the immense scale and breadth of Adobe’s needs in content understanding, processing, and discovery, powering generative AI agents and the world’s leading creative tools.
You will be responsible for designing, developing, and deploying large-scale machine learning systems that directly impact millions of users and billions of content pieces. You will work in a start-up like environment with the opportunity to push the boundaries of what’s possible in generative AI, language models, and assistive experiences, all within the supportive infrastructure and resources of Adobe.
Responsibilities:
System Design & Development: Define and develop end-to-end machine learning systems using innovative architectures
Model Optimization & Deployment: Develop and implement scalable, GPU-optimized modeling algorithms capable of handling large-scale data in production environments.
Pipeline Development: Build and maintain high-performance, scalable, and maintainable platform features throughout the complete ML pipeline.
Collaboration & Communication: Partner with architects, product management, and engineering teams to translate product requirements into innovative technical solutions
Emerging Technologies: Design and develop runtimes and libraries for emerging ML technologies, ensuring we remain at the forefront of the field.
Documentation & Review: Contribute to the creation of detailed requirements and design documents for features across the technology stack.
What You Need to Succeed:
Education: PhD or master’s degree in computer engineering, Computer Science, Computer Vision, Robotics, or a related field, or equivalent experience.
Technical Expertise: Deep understanding of generative AI, deep learning, computer vision, and recommendation systems, with a proven track record of applying these methods to solve complex problems.
Proficiency with machine learning frameworks and tools such as Scikit-learn, Hugging Face, PyTorch, and PyTorch Lightning.
Expertise with cloud technologies, Docker, and containerization.
Experience with AWS, Microsoft Azure, or equivalent cloud platforms.
Proficiency in one or more programming languages, including Python, C++, Java, and Rust.
Strengths you’ll need:
Exceptional analytical and quantitative problem-solving skills.
Excellent communication, interpersonal, and relationship-building skills.
Demonstrated ability to thrive in a collaborative team environment.
About Adobe
Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.
Let’s Adobe together
At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create.
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.
Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com .
AI Use Guidelines for Interviews:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .
Expected Pay Range: Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $151,800 - $265,350 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
In California, the pay range for this position is $183,300 - $265,350
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
State-Specific Notices:
California :
Fair Chance Ordinances
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Colorado:
Application Window Notice
If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.
Massachusetts:
Massachusetts Legal Notice
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
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Find Machine Learning Intern JobsMachine Learning Intern Job Market in San Jose
Who's Hiring
- TikTok448

- ByteDance121

- Adobe101

- TikTok USDS JV43
- TikTok USDS Joint Venture24

Top Industries Hiring
- Technology & Software169
- Media & Entertainment10
- Electronics & Hardware10
- Fintech5
- Social Media5
Machine Learning Intern Jobs in San Jose: Frequently Asked Questions
How do I get a machine learning intern job in San Jose?
The strongest path into a machine learning intern role in San Jose runs through the city's semiconductor and enterprise software clusters in North San Jose and the Alviso corridor. Employers in these sectors prioritize candidates with hands-on Python or PyTorch experience and at least one completed ML project. Targeting mid-size AI infrastructure firms alongside the larger tech employers gives you a real edge, since competition for marquee-name internships is intense.
Which companies hire machine learning interns in San Jose?
San Jose machine learning intern roles are posted by TikTok, ByteDance, and Adobe and others right now, based on current listings on Migrate Mate as of September 2026. San Jose's employer base skews heavily toward semiconductor companies, enterprise cloud platforms, and AI-focused hardware firms, making it one of the denser local markets for applied ML internship work.
Are there remote machine learning intern jobs in San Jose?
Yes, though availability depends on the work. Machine learning intern roles tied to hardware validation or lab access are almost always on-site, while data pipeline, model training, and analytics-focused positions are more likely to offer flexibility. About 26% of machine learning intern openings tied to San Jose are remote or hybrid as of September 2026, with hybrid arrangements most common at enterprise software employers in the Downtown and North San Jose corridors.
How can I get a machine learning intern job in San Jose with little or no experience?
The most realistic entry path in San Jose is through research internships at institutions like San Jose State University or through junior data analyst roles at mid-size enterprise software firms that funnel strong performers into ML tracks. Building a public portfolio of completed projects on GitHub and targeting smaller AI startups in North San Jose, where teams move faster and rely more on generalist contributors, gives candidates without formal work history a concrete foothold.
Which industries hire the most machine learning interns in San Jose?
The sectors hiring the most machine learning interns in San Jose are Technology & Software, Media & Entertainment, and Electronics & Hardware, based on current listings on Migrate Mate as of September 2026. San Jose's position as a center for semiconductor design and enterprise cloud infrastructure means local ML intern demand is driven heavily by applied research and product development work rather than purely analytical roles.
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