Machine Learning Manager Jobs in San Jose, CA
Machine Learning Manager jobs in San Jose are in high demand, concentrated in North San Jose, Downtown, and the Alviso and Coyote Valley tech corridors, across semiconductor, enterprise software, and cloud infrastructure sectors. Employers hiring right now include TikTok, ByteDance, and Adobe. See the openings below and apply to the ones that match your experience.
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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 Manager JobsMachine Learning Manager Job Market in San Jose
Who's Hiring
- TikTok452

- ByteDance124

- Adobe104

- TikTok USDS JV45
- TikTok USDS Joint Venture25

Top Industries Hiring
- Technology & Software169
- Media & Entertainment10
- Electronics & Hardware10
- Fintech5
- Social Media5
Machine Learning Manager Jobs in San Jose: Frequently Asked Questions
How do I get a machine learning manager job in San Jose?
The strongest path into a machine learning manager role in San Jose runs through the city's dense semiconductor and enterprise software ecosystem, particularly in North San Jose and the Alviso corridor. Candidates who combine hands-on model deployment experience with cross-functional team leadership stand out here. Targeting mid-size AI infrastructure companies alongside the large chipmakers broadens your options, and familiarity with Silicon Valley-style product-driven ML workflows gives you a concrete edge in interviews.
Which companies hire machine learning managers in San Jose?
San Jose machine learning manager 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 hiring base skews toward semiconductor firms, enterprise cloud platforms, and cybersecurity companies with large in-house ML teams rather than consumer-facing startups.
Are there remote machine learning manager jobs in San Jose?
Yes, though availability depends on the role's focus, since machine learning manager positions that involve on-site hardware, data center access, or close lab collaboration tend to require in-person presence. About 27% of machine learning manager openings tied to San Jose are remote or hybrid as of September 2026, reflecting a mix of flexible options. Roles centered on model strategy, team oversight, and research coordination are the most commonly offered as remote in San Jose.
How can I get a machine learning manager job in San Jose with little or no experience?
The most realistic entry path in San Jose is stepping into a senior ML engineer or tech lead role at one of the city's mid-size AI or semiconductor companies first, then transitioning into management internally. San Jose employers like chipmakers and enterprise software firms frequently promote from within rather than hiring first-time managers externally. Building a record of mentoring junior engineers and owning end-to-end model pipelines makes that internal move significantly easier to make.
Which industries hire the most machine learning managers in San Jose?
Most machine learning manager openings in San Jose sit in Technology & Software, Media & Entertainment, and Electronics & Hardware, per current listings on Migrate Mate as of September 2026. San Jose's position as a global center for chip design, enterprise networking, and cloud infrastructure means those sectors generate consistent, year-round demand for managers who can bridge research and production ML systems.
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