Overview

Chances are, you’ve emitted millions of digitally recorded data points today and interacted with at least 3 network-connected devices. Cybersecurity practitioners already struggle to manage threats, vulnerabilities, and risk in current-state environments. Industry projections on the proliferation of connected devices and data elements are leading us into a landscape where breaches are commonplace, and security practitioners are stuck trying to maintain a seemingly infinite number of issues or events.

At Rapid7, you’re focused on solving this problem by utilizing AI/Deep Learning methods to enhance and automate intelligent decision-making for practitioners. You are passionate about incrementally improving security through these approaches and creating tools that enable defenders to detect, deter and contain attackers. You strive to build meaningful relationships with customers, Rapid7 employees, and research partners across the globe; these relationships become the foundation of teamwork that will result in better technology to solve these challenging security problems.

As part of Rapid7 Labs, you will collaborate with a globally distributed, core team of Data Scientists, Systems/Data Engineers, and Security Researchers. Your work will not only touch customers directly through products and services we create, but you will be a defining voice on the forefront of Artificial Intelligence/Deep Learning and their applications to cybersecurity to the outside world through publications and conferences. You will have opportunities to apply your skill set to tough problems in vulnerability management & prioritization, anomalous behaviour identification, web application security, threat hunting, and internet-scale adversary identification/tracking. Ultimately, the outcome of your work will be to enable scores of defenders across thousands of organizations to work better, faster, and smarter.

Responsibilities:

• Develop AI/DL-based solutions for real world, large scale cybersecurity problems
• Evangelize a unique perspective on cybersecurity issues through research, speaking engagements, and publications
• Assess, understand and analyze diverse data sources including sampling biases, accuracy, coverage, and potential model limitations
• Collaborate with data engineers to identify data preparation/cleansing/ETL pipelines
• Spearhead critical initiatives from concept to rapid prototype to go/no-go

Qualifications:

• PhD in AI, Deep Learning, Computer Science, a related technical field, or equivalent practical experience
• Demonstrated knowledge of model development with PyTorch, Keras, TensorFlow, or other modern learning frameworks
• Experience developing production-quality CNNs, RNNs, and/or GANs
• Programming experience and proficiency in one or more of the following: R, Python, Java, Scala
• Experience with generating and publishing research content for diverse audiences
• Proven track record in generating AI-driven models and applying them to practical issues
• Experience with SQL, Spark, Athena, Presto, Drill, Hive, relational databases, NoSQL databases, and API endpoints

Preferred, but not required:

• Experience with cybersecurity, including network protocols, malware concepts, risk assessments, botnet concepts, and anomaly detection

• Active contributions to open source communities