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Machine Learning Engineer

San Jose, California, United States of America

Pay
Multiple pay statements — pay source
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 $125,600 - $234,150 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 $161,700 - $234,150
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 $125,600 - $234,150 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 $161,700 - $234,150 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).
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Work setup
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Employment
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What you’ll work on

Full posting
  • You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team.

  • Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs.

  • Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring.

From the employer’s posting
Adobe is seeking a Machine Learning Engineer to join the Adobe Risk Platform (ARP) team. ARP is Adobe's centralized, adaptive system for detecting, preventing, and mitigating fraud and abuse across products and services — protecting surfaces like Commerce, Stock, and Firefly with real-time risk decisions, without degrading the customer experience. In this position, you will help build and develop machine learning models to identify fraudulent activity, detect abusive account behavior, and protect the experience of hundreds of millions of users. You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team. Key Responsibilities
Contribute to feature engineering across transaction, device, and behavioral event data. Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs. Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability.
Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability. Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams to understand fraud and abuse patterns across Adobe's surfaces.

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience).
  • 3+ years of professional experience building and deploying ML solutions, or equivalent experience through internships, research, or personal projects.

Preferred experience

  • Familiarity with Databricks, Spark, or large-scale transactional/event pipelines.
Qualification wording
Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience).
3+ years of professional experience building and deploying ML solutions, or equivalent experience through internships, research, or personal projects.
Familiarity with Databricks, Spark, or large-scale transactional/event pipelines.

Tools in this posting

  • Python
  • Databricks
  • Spark
  • PyTorch
  • TensorFlow
  • scikit-learn
Source — Tool mentions in context
- 3+ years of professional experience building and deploying ML solutions, or equivalent experience through internships, research, or personal projects. - Solid programming skills in Python, with hands-on experience in PyTorch, TensorFlow, scikit-learn, or similar frameworks. - Working understanding of the ML lifecycle — from data collection through deployment and monitoring.
- Contribute to feature engineering across transaction, device, and behavioral event data. - Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs. - Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability.
- Exposure to sequence modeling, transformer architectures, or graph neural networks. - Familiarity with Databricks, Spark, or large-scale transactional/event pipelines. About Adobe

About Adobe

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.

In the employer’s words · Read in context

Job description

View original posting ↗

Adobe is seeking a Machine Learning Engineer to join the Adobe Risk Platform (ARP) team. ARP is Adobe's centralized, adaptive system for detecting, preventing, and mitigating fraud and abuse across products and services — protecting surfaces like Commerce, Stock, and Firefly with real-time risk decisions, without degrading the customer experience.

In this position, you will help build and develop machine learning models to identify fraudulent activity, detect abusive account behavior, and protect the experience of hundreds of millions of users. You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team.

Key Responsibilities

  • Help build and train ML models covering various fraud and abuse areas. These include financial transaction fraud, device-related deception, and account and identity abuse. The goal is a unified, continuously-updated trust and risk score.
  • Contribute to feature engineering across transaction, device, and behavioral event data.
  • Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs.
  • Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability.
  • Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring.
  • Collaborate cross-functionally with data science, product, and platform teams to understand fraud and abuse patterns across Adobe's surfaces.
  • Stay ahead of advances in ML/AI, particularly in fraud detection and behavioral modeling, and bring relevant ideas to the team.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience).
  • 3+ years of professional experience building and deploying ML solutions, or equivalent experience through internships, research, or personal projects.
  • Solid programming skills in Python, with hands-on experience in PyTorch, TensorFlow, scikit-learn, or similar frameworks.
  • Working understanding of the ML lifecycle — from data collection through deployment and monitoring.
  • Eagerness to learn model optimization, inference efficiency, and production system integration, with support from senior engineers on the team.

Preferred Qualifications

  • Coursework, projects, or professional experience in any of: payment fraud, device fingerprinting, account takeover detection, anomaly detection, or graph-based modeling.
  • Exposure to sequence modeling, transformer architectures, or graph neural networks.
  • Familiarity with Databricks, Spark, or large-scale transactional/event pipelines.

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 $125,600 - $234,150 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 $161,700 - $234,150

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

Oct 30 2026 12:00 AM

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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  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

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Source & posting history

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Pay
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 $125,600 - $234,150 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 $161,700 - $234,150
More source context
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 $125,600 - $234,150 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 $161,700 - $234,150 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).
Location & working pattern

San Jose, California, United States of America

Working pattern and location restrictions need checking in the full posting.

Work authorization

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Status in our records
Active
First seen by us
Sep 12, 2026
Recorded sightings
83
Last seen by us
Oct 9, 2026

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