Sr Machine Learning Engineer, WAF Detection

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. 

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

 

The Opportunity

We are on the lookout for a proficient and forward-thinking Machine Learning Engineer to join our Product Security Engineering organization. This role offers the opportunity to create, innovate, and implement machine learning models and analytical systems that enhance our Web Application Firewall (WAF) capabilities. Your contributions will directly enhance our ability to defend against emerging web threats, resulting in a significant improvement in our security posture.

What You'll Do

• 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 operation.
• Partner with security engineers, product managers, and development teams to understand security challenges, translate them into machine learning problems, and integrate solutions into our core products.
• Stay current with the latest 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 to implementation, testing, deployment, and ongoing maintenance.

What You Need to Succeed

• Experience in a software engineering or machine learning role within a cloud security or cybersecurity context.
• Proven ability in crafting and deploying machine learning models, algorithms, and analytical systems, particularly tailored for security-related purposes.
• 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 strong interest in developing algorithms and heuristics.
• Strong knowledge of machine learning algorithms, statistics, and predictive modeling
• Experience with machine learning operations (MLOps) and productionization of ML models.
• Familiarity with building data and metric generation pipelines, using tools like SQL or Spark, to answer business questions and assess system efficacy.
• Ability to communicate complex technical ideas in a clear, non-technical manner.

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 $140,100 -- $245,700 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.

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.

S