Senior AI / Machine Learning Engineer — Fraud Prevention

Adobe; Texas; Hybrid; USD 152,000 - 265,000; Full time

Job summary

Adobe is seeking a Senior AI/ML Engineer to build and operate fraud detection and abuse systems, applying anomaly detection, risk analysis, and AI/LLM-enabled capabilities. You will own end-to-end solutions from signals to production deployment and real-time decisioning, with impact across product, risk, and engineering teams.

The role blends hands-on ML, data, and backend work, requires 8+ years of production ML experience, strong Python/SQL and PyTorch skills, and a bias for ownership in a

Qualifications

• Production ML experience in fraud/risk/adversarial domains.
• Strong Python, SQL and PyTorch skills.
• Experience bringing ML systems from feature engineering to production deployment and monitoring.

Responsibilities

• Build and deploy high‑precision ML models for fraud and abuse detection, anomaly detection, and risk scoring.
• Engineer risk signals from large‑scale account, device, network, behavioral, velocity, and session data.
• Integrate ML/AI features into real‑time risk decisioning and automated enforcement systems.
• Apply LLMs and AI agents to expand detection, investigation, and classification capabilities.
• Translate emerging attack patterns and relevant research into new models, signals, and mitigations.
• Evaluate solutions across accuracy, latency, cost, and customer impact.
• Own model evaluation, monitoring, and drift as attacker behavior evolves.
• Partner across engineering, product, and risk teams to ship production‑ready capabilities.

Skills

Production ML systems

Python

SQL

PyTorch

LLMs / AI agents

Adversarial risk understanding

Ownership & accountability

Education

Bachelor's degree in CS/Statistics/Math

Tools

PyTorch

LLMs

Job description

Senior AI / Machine Learning Engineer — Fraud Detection

The Opportunity

We are in search of an experienced Senior AI/ML Engineer to develop and broaden fraud and abuse detection systems. You will improve ML techniques in anomaly detection, user/device risk analysis, identity and service abuse, and evolving AI abuse scenarios.

This is a hands‑on role spanning ML, data, and backend systems, with opportunities to apply LLMs, AI agents, and modern ML techniques to strengthen detection. You will own solutions end to end — from signals and modeling through production deployment and real‑time decisioning. Join us in crafting best in class fraud detection systems that will make a significant impact!

What you'll Do

• Build and deploy high‑precision ML models for fraud and abuse detection, anomaly detection, and risk scoring.
• Engineer risk signals from large‑scale account, device, network, behavioral, velocity, and session data.
• Integrate ML/AI features into real‑time risk decisioning and automated enforcement systems.
• Apply LLMs and AI agents to expand detection, investigation, and classification capabilities.
• Translate emerging attack patterns and relevant research into new models, signals, and mitigations.
• Evaluate solutions across accuracy, latency, cost, and customer impact.
• Own model evaluation, monitoring, and drift as attacker behavior evolves.
• Partner across engineering, product, and risk teams to ship production‑ready capabilities.

What you'll need to succeed

• 8+ years building and operating production ML systems, ideally in fraud, abuse, risk, identity, trust & safety, or other adversarial domains.
• Solid ML background with practical experience in Python, SQL, and current ML frameworks like PyTorch.
• Experience guiding ML systems from feature engineering to production deployment and monitoring.
• Strong software/data engineering skills across ML, backend, and data infrastructure.
• Experience building with LLMs and/or AI agents, particularly for AI/generation‑abuse use cases.
• Strong technical judgment, ownership, and ability to solve ambiguous, adversarial problems.
• Bachelor's or equivalent experience in Computer Science, Statistics, Mathematics, or related field; advanced degree a plus.

Preferred Attributes

• Device fingerprinting, identity verification, behavioral signals, network intelligence, or VPN/proxy detection.
• Real‑time risk evaluation and automated control systems.
• Human‑in‑the‑loop or AI‑assisted evaluation systems.
• Distributed systems and high‑scale data pipelines.
• Strong adversarial approach — anticipating how attackers adapt to mitigations.

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 [e-mail].

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. In New York, the pay range for this position is $183,300 - $265,350. In Illinois, the pay range for this position is $156,300 - $226,350. In Washington, the pay range for this position is $165,600 - $239,725.

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.