Sr Applied AI/ML Engineer, Product Security Engineering

Position Overview

Changing the world through digital experiences is what Adobe's all about. We empower everyone—from emerging artists to global brands—to create beautiful and powerful images, videos, and apps, transforming how companies interact with customers across every screen. We are on a mission to hire the very best and are committed to creating an exceptional employee experience built on respect and equal opportunity.

We are seeking a proficient and forward-thinking Machine Learning Engineer to join our Product Security Engineering organization. In this role, you will create, innovate, and implement machine learning models and analytical systems that enhance our Web Application Firewall (WAF) capabilities and strengthen our defense against emerging web threats.

Salary: The U.S. pay range for this role is $144,800 -- $261,450 annually. In California, the range is $180,600 - $261,450; in Washington, it is $170,900 - $247,550. Additional compensation may include long-term incentives and bonus structures based on role and performance.

Key Responsibilities

• Lead the development and implementation of novel machine learning systems and algorithms to analyze web traffic and generate intelligent WAF rule recommendations.
• Develop and deploy models that identify and mitigate advanced web-based attacks (e.g., OWASP Top 10 threats, bot attacks, DDoS) based on behavioral patterns.
• Work with large-scale, real-time data from WAF logs using platforms like Databricks for data engineering, processing, and analysis for model training and feature engineering.
• Architect and build cloud-native, scalable microservice infrastructures to support machine learning pipelines, ensuring high performance and low latency.
• Partner with security engineers, product managers, and development teams to translate security challenges into machine learning problems and integrate innovative solutions.
• Stay current with emerging research in machine learning and cybersecurity, driving the development of new, patent-worthy applications for threat detection.
• Take ownership of projects from initial prioritization and requirements gathering through implementation, testing, deployment, and ongoing maintenance.

Required Qualifications

• Experience in a software engineering or machine learning role within a cloud security or cybersecurity context.
• Proven ability to craft and deploy machine learning models, algorithms, and analytical systems tailored for security-related challenges.
• Strong programming skills in Python and/or Go.
• Hands-on experience with cloud providers such as AWS and/or GCP, including familiarity with services like EC2, S3, Kubernetes, and serverless functions.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Proficiency with Infrastructure as Code (IaC) tools such as Terraform.
• Experience working with data platforms, such as Databricks, for data processing and analysis.
• Familiarity with log aggregation and analysis platforms like Splunk.
• Strong understanding of web technologies, including WAFs, CDNs, and DDoS mitigation.
• Excellent problem-solving skills and a keen interest in developing innovative algorithms and heuristics.
• Solid knowledge of machine learning algorithms, statistics, and predictive modeling.
• Experience with machine learning operations (MLOps) and productionizing ML models.
• Familiarity with building data and metric generation pipelines using tools like SQL or Spark to address business questions and assess system efficacy.
• Ability to communicate complex technical ideas in a clear, non-technical manner.