Senior Software Engineer - Attack Detection

Posted 12 Days Ago
Be an Early Applicant
Hiring Remotely in Canada
Remote
5-7 Years Experience
Security • Cybersecurity
The Role
As a Senior Software Engineer on the Attack Detection team, you'll design and build backend services for a high recall Detection Engine, optimize models for low latency, and mentor junior engineers. Collaborating with ML engineers, you'll help architect a robust ML platform.
Summary Generated by Built In

About the Role

Abnormal Security is looking for a Senior Software Engineer to join the Message Detection - Attack Detection team.  At Abnormal, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Security. That’s what makes our novel behavioral-based approach so…Abnormal. Abnormal has constantly been named as one of the top cybersecurity startups and our behavioral AI system has helped us win various cybersecurity accolades resulting in being trusted to protect more than 8% of the Fortune 1000 ( and ever growing ).

In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories.

This team is solving a multi-layered detection problem, which involves modeling communication patterns to establish enterprise-wide baselines, incorporating these patterns as robust signals, and combining these signals with contextual information to create extremely precise systems. The team builds discriminative signals at various levels including message level (eg. presence of particular phrases), sender-level (eg.frequency of sender) and recipient level (eg.likelihood of receiving a safe message). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. In order 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.

This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. 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.

What you will do

  • 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 generally 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

Must Haves

  • 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 cyber security industry


#LI-RT1

Top Skills

Python
The Company
San Francisco, CA
175 Employees
On-site Workplace
Year Founded: 2018

What We Do

The Abnormal Security platform protects enterprises from targeted email attacks. Abnormal Behavior Technology (ABX) models the identity of both employees and external senders, profiles relationships and analyzes email content to stop attacks that lead to account takeover, financial damage and organizational mistrust. Though one-click, API-based Office 365 and G Suite integration, Abnormal sets up in minutes and does not disrupt email flow.
Abnormal Security was founded in 2018 by CEO Evan Reiser, CTO Sanjay Jeyakumar, Head of Machine Learning Jeshua Bratman, and Founding Engineers Abhijit Bagri and Dmitry Chechik. The team previously built behavioral profiling and machine learning technologies at Twitter, Google and Pinterest that are being applied to solve a problem that costs organizations $1 billion per year, according to the FBI. The Abnormal Security platform stops targeted phishing, business email compromise and account takeover attacks that have never been seen before.

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