# Senior AI / Machine Learning Engineer — Fraud Detection

**Company**: Adobe
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $151,800 - $265,350 annually
**Category**: Engineering
**Industry**: Technology

**Apply**: https://adobe.wd5.myworkdayjobs.com/en-US/external_experienced/job/San-Jose/Senior-AI---Machine-Learning-Engineer---Fraud-Detection_R171801-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_69c21c67-cd9

## Description

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!

**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.

**Requirements**

- 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.

**Benefits**

- Hybrid Work Model: This role follows a hybrid schedule, with a minimum of 3 days per week in the office.

- Comprehensive benefits programs

- Opportunities for professional growth and development

## Skills

### Required
- Python
- SQL
- PyTorch
- Machine Learning
- Artificial Intelligence

### Nice to have
- LLMs
- AI agents
- device fingerprinting
- identity verification
- behavioral signals
- network intelligence
- VPN/proxy detection

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Source: [Apply at adobe.wd5.myworkdayjobs.com](https://adobe.wd5.myworkdayjobs.com/en-US/external_experienced/job/San-Jose/Senior-AI---Machine-Learning-Engineer---Fraud-Detection_R171801-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)