Cybersecurity Threat Detection Architect
1 week ago
Abnormal Security is a leading cybersecurity company that protects its customers from nefarious adversaries.
About the RoleWe are seeking an experienced Cybersecurity Threat Detection Architect to join our Message Detection - Attack Detection team. Our novel behavioral-based approach has helped us win various cybersecurity accolades and protect over 8% of the Fortune 1000.
In a landscape where a single successful attack can lead to financial losses of millions of dollars, our team plays a central role in building a high-recall detection engine that operates at milliseconds latency. Our mission statement is to provide world-class detector efficacy using a combination of generalizable and auto-trained models, as well as specific detectors for high-value attack categories.
This team solves a multi-layered detection problem by modeling communication patterns, incorporating these patterns as robust signals, and combining them with contextual information to create precise systems. We build discriminative signals at various levels, including message level, sender level, and recipient level, which are then combined and utilized to train highly accurate model-based and heuristic detectors.
To ingest, evaluate, and build on these signals, it is critical to have a robust ML platform that scales to meet the needs of our customers. As a Senior Software Engineer, you will collaborate with machine learning engineers to architect an ML platform that enables development and deployment of large ML models with low latency.
Your Responsibilities- Architect, design, build, and deploy backend services and infrastructure that support a world-class Detection Engine.
- Owning impactful projects such as building and improving our feature store, optimizing models to run with lower latency/memory requirements, and being the bridge between our ML and platform teams.
- Coach and mentor junior engineers via 1on1s, pair programming, high-quality code reviews, and design reviews.
Requirements
- 5+ years of professional experience as a hands-on engineer building data-oriented products.
- Experience with real-time, online, and/or high-throughput & low-latency distributed systems.
- Works well with other stakeholders - has worked with cross-functional teams to drive projects over the finish-line.
- High standards - sets high standards and expectations for project execution for themselves and for collaborators.
- BS degree in Computer Science, Applied Sciences, Information Systems, or other related engineering field.
Nice to Haves
- Knowledge of ML systems/products and/or distributed system technologies (feature platform serving systems, ML training and ML serving platforms, etc.).
- Experience working with high-throughput offline systems in Python and/or Go.
- MS degree in Computer Science, Electrical Engineering, or other related engineering field.
- Familiarity with cybersecurity industry.
We offer a competitive base salary range of $176,000—$207,000 USD, eligibility for bonus and restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications, and other job-related reasons.
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