Machine Learning Scientist Jobs in San Jose, CA
Machine Learning Scientist jobs in San Jose are concentrated in North San Jose, Downtown, and the Santana Row corridor, with strong demand across semiconductor, enterprise software, and cloud infrastructure sectors. Employers hiring right now include TikTok, ByteDance, and Adobe. Find a role that fits below and apply directly.
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We are seeking an experienced Senior Machine Learning Data Scientist to build fraud and abuse detection models and measure how effectively they work. This role combines hands-on modeling with deep experimentation, evaluation, and analytics to improve detection and quantify business impact.
You will work across the fraud lifecycle — from modeling and ground-truth definition to performance measurement, monitoring, and executive-ready insights! What you'll Do
Build and tune ML models for fraud and abuse detection using statistical and classical ML techniques.
Develop robust evaluation frameworks, datasets, and metrics to measure model and mitigation effectiveness.
Analyze false positives/negatives, model drift, and emerging fraud patterns to continuously improve detection.
Define ground truth, labeling approaches, and fraud taxonomies that support reliable model development and evaluation.
Design experiments and evaluate tradeoffs across precision, recall, customer impact, and fraud loss.
Build dashboards and metrics that translate detection performance into measurable business impact.
Pressure-test models and data for leakage, bias, data-quality issues, and other sources of misleading results.
Partner across engineering, product, policy, and risk teams to turn insights into detection improvements and business decisions. What you'll need to succeed
8+ years in applied Data Science / ML, with experience building and evaluating production ML models.
Strong foundation in statistical and classical ML, experimentation, model evaluation, and performance measurement.
Strong hands-on Python and SQL skills working with large, complex datasets.
Experience with model monitoring, drift, false-positive/false-negative analysis, and imperfect or delayed labels.
Strong data visualization and storytelling skills — able to translate complex analysis into clear insights and recommendations.
Strong analytical judgment, ownership, and ability to operate independently through ambiguity.
Bachelor's or equivalent experience in Statistics, Mathematics, Computer Science, or related field; advanced degree a plus. Preferred Attributes
Experience in fraud, abuse, risk, identity, trust & safety, or other adversarial domains.
Experience with anomaly detection, clustering, behavioral modeling, or prevalence estimation.
Experience with labeling frameworks, weak supervision, active learning, or human-review systems.
Familiarity with LLMs and AI-assisted evaluation/analysis.
Experience evaluating multi-layered risk controls and automated decisioning systems.
Hybrid Work Model: This role follows a hybrid schedule, with a minimum of 3 days per week in the office.
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 $133,100 -- $236,400 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 $163,200 - $236,400
In New York, the pay range for this position is $163,200 - $236,400
In Illinois, the pay range for this position is $149,100 - $216,000
In Washington, the pay range for this position is $157,900 - $228,575
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
There is no deadline to apply to this job posting because Adobe accepts applications for this role on an ongoing basis. The posting will remain open based on hiring needs and position availability.
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.
See All 88 Machine Learning Scientist Jobs in San Jose
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Find JobsMachine Learning Scientist Job Market in San Jose
Who's Hiring
- TikTok48

- ByteDance24

- Adobe16

Top Industries Hiring
- Technology & Software16
- Social Media8
- Media & Entertainment8
Machine Learning Scientist Jobs in San Jose: Frequently Asked Questions
How do I get a machine learning scientist job in San Jose?
The strongest path into San Jose's market is targeting the semiconductor and enterprise AI companies that anchor North San Jose and the Alviso corridor, where ML research and applied modeling roles concentrate. Candidates who combine deep learning expertise with domain knowledge in chip design, computer vision, or large-scale recommendation systems stand out. Presenting published work, open-source contributions, or demonstrable production model deployments gives you a concrete edge over applicants with only academic credentials.
Which companies hire machine learning scientists in San Jose?
Companies currently hiring machine learning scientists in San Jose include TikTok, ByteDance, and Adobe, per current listings on Migrate Mate as of September 2026. San Jose's hiring landscape skews toward large semiconductor firms, enterprise software developers, and AI-native startups that have established R&D offices in the city's North San Jose and Downtown tech corridors.
Are there remote machine learning scientist jobs in San Jose?
Yes, though remote availability varies: research-heavy and applied modeling roles at San Jose employers are often on-site due to cluster computing infrastructure and team collaboration requirements. About 20% of machine learning scientist openings tied to San Jose are remote or hybrid as of September 2026, with hybrid arrangements most common for data pipeline, experimentation, and model evaluation work that doesn't require direct hardware access.
How can I get a machine learning scientist job in San Jose with little or no experience?
The most realistic entry path in San Jose is through associate or junior ML engineer roles at mid-size enterprise software companies in the Downtown and North San Jose corridors, which tend to have more structured onboarding than large semiconductor firms. San Jose's proximity to San Jose State University means local employers regularly recruit through cooperative education programs and research partnerships. Building a portfolio of reproducible ML projects and contributing to open-source frameworks used by local companies strengthens any early-career application.
Which industries hire the most machine learning scientists in San Jose?
Most machine learning scientist openings in San Jose sit in Technology & Software, Social Media, and Media & Entertainment, per current listings on Migrate Mate as of September 2026. San Jose's position as the center of Silicon Valley's semiconductor cluster and enterprise software ecosystem drives this concentration, with AI-integrated product development and chip optimization creating sustained demand for ML research talent across those sectors.
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