Machine Learning Engineer

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.

• →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.

• 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.

• 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.

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. 

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.

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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.

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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.

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