companyAbnormal Security logo

Machine Learning Engineer II at Abnormal Security | Remote

Abnormal SecurityRemote - USA
Remote Full-time $168.3K/yr - $198K/yr

Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.


Unlock Your Potential

Generate Job-Optimized Resume

One Click And Our AI Optimizes Your Resume to Match The Job Description.

Is Your Resume Optimized For This Role?

Find Out If You're Highlighting The Right Skills And Fix What's Missing

Experience Level

Mid to Senior

Qualifications

What You Will Do Design and implement cutting-edge systems that enhance detection capabilities. Collaborate with cross-functional teams to refine model accuracy and efficiency. Conduct research to stay ahead of emerging threats and adapt detection strategies accordingly. Engage in continuous learning to improve personal and team knowledge in machine learning and cybersecurity.

About the job

About The Role

At Abnormal AI, we are on a mission to redefine security with our innovative Machine Learning Engineer role within the Message Detection - Attack Detection team. Our focus is to shield our clients from evolving threats posed by malicious actors who continuously adapt their tactics to bypass conventional security measures. Our unique behavioral-based approach sets us apart, and we take pride in being recognized as one of the top cybersecurity startups. Our advanced behavioral AI system has earned us numerous cybersecurity accolades, allowing us to safeguard over 25% of the Fortune 500 and counting.

In a world where a single successful cyberattack can result in losses amounting to millions, our Attack Detection team is pivotal in constructing a high-recall Detection Engine capable of analyzing hundreds of millions of messages with minimal latency. Our mission is to deliver exceptional detector efficacy to effectively address the dynamic threat landscape by utilizing a blend of generalizable and auto-trained models alongside specialized detectors for critical attack categories.

We tackle a complex detection challenge involving the modeling of communication patterns to establish enterprise-wide baselines. By integrating these patterns as robust signals and combining them with contextual data, we create highly precise detection systems. The team develops discriminative signals at multiple levels, including message-level (e.g., identifying specific phrases), sender-level (e.g., analyzing sender frequency), and recipient-level (e.g., evaluating the likelihood of receiving a secure message). These signals are then synthesized to train both model-based and heuristic detectors. Furthermore, to continuously adapt to emerging threats, we implement various stages in our automated model retraining pipelines, including data analytics, modeling, production evaluation, and automated deployment.

This position offers a unique opportunity to significantly influence the team’s direction, charter, and roadmap. As a Machine Learning Engineer, you will delve into the domain of false negatives, identifying current and potential future attacks that could disrupt customer workflows. You will play a crucial role in defining the technical roadmap needed to tackle pressing customer challenges while ensuring the optimal operation of our detection decisioning system at an exceptionally high recall rate.

About Abnormal Security

Abnormal Security is at the forefront of cybersecurity innovation, leveraging advanced AI technologies to protect businesses from sophisticated threats. Our commitment to excellence has earned us accolades and recognition as a leading startup in the industry, providing unparalleled security solutions to Fortune 500 companies and beyond.

Similar jobs

Tailoring 0 resumes

We'll move completed jobs to Ready to Apply automatically.