Machine Learning Engineer, Cloudforce One Threat Intelligence

Available Locations: London, UK

About the Team

Cloudforce One is Cloudflare’s threat operations and research team, responsible for identifying and disrupting cyber threats ranging from sophisticated cyber criminal activity to nation-state sponsored advanced persistent threats (APTs). Cloudforce One works in close partnership with external organizations and internal Cloudflare teams, continuously developing operational tradecraft and expanding ever-growing sources of threat intelligence to enable expedited threat hunting and remediation. Members of Cloudforce One are at the helm of leveraging an incredibly vast and varied set of data points that only one of the world’s largest global networks can provide. The team is able to analyze these unique data points, at massive scale and efficiency, synthesizing findings into actionable threat intelligence to better protect our customers. The team's core disciplines are data engineering, data science, devops, and security. We use data science and machine learning to process large volumes of data and build threat intelligence for Cloudflare's customers

About the Role

We're looking for a Machine Learning Engineer to join our team and lead the charge in applying cutting-edge machine learning to cyber threat intelligence. In this highly impactful, hands-on role, you'll design, develop, and deploy scalable machine learning models that leverage massive datasets from our global network to identify and neutralize sophisticated cyber threats. Your expertise will directly enhance our Cloudforce One offering, providing critical, real-time insights and unparalleled protection to our customers. If you're driven to solve complex cybersecurity challenges at an unprecedented scale, we want you on our team.

The candidate should have strong foundational machine learning knowledge. Day to day responsibilities include:

• Collaborate with other Data Scientists and Machine Learning Engineers to integrate and deploy scalable Machine Learning models
• Collaborate with analysts to understand new email attack techniques then design and deploy models to detect these techniques
• Implement Machine Learning models in production systems and monitor their performance in real-time.
• Continuously improve the performance and scalability of existing Machine Learning models.
• Identify, diagnose and resolve issues in production environments

Examples of desirable skills, knowledge and experience

• Thorough understanding of machine learning concepts such as what types of models perform best again what types of data
• Desire to see a project through all the way from model creation, training, productionalized deployment, through automated retraining from feedback
• Demonstrated ability to deliver and listen to feedback.
• Proven ability to deliver performance (what) with the right behaviors (how)

Bonus Points

These are things which the role is likely to require; we’re happy to help you learn on the job, but prior experience is beneficial

• Experience with deploying Deep Learning models in production systems
• Experience with development and deployment of Natural Language Processing (NLP) applications
• Wide machine learning knowledge from linear regression through LLMs
• A basic understanding of the cyber threat landscape and technical Indicators of Compromise (IOCs)