Machine Learning Engineer [US or Canada]

Machine Learning Engineer [US or Canada]

This job is no longer open

About Abnormal Security

Users and companies are constantly under attack but Abnormal Security’s team and patented, ML-first approach is redefining email security for the next generation. Our incredible team needs your help to keep ahead of the evolving threats facing the world. We tackle critical challenges using novel approaches and modern technologies that help make the world a safer place.

Call us Abnormal, but tackling impossible problems takes partnership with customers. By listening to what they want we can build them what they need to stop adversarial cybercrime. It also means our customers love what we build for them because it solves the problems that matter to them! And, of course, it is beautiful to look at and easy to use and administer!

But it’s not just our products; we are Abnormal too.

We’ve combined some of the best talent in the world with serially successful & passionate leadership, which gives us the ability to tackle complex challenges, build incredible things, and experiment and iterate quickly! Then, we empower our people to take ownership of complex end-to-end problems in a culture that supports and rewards them.

Come see what’s so great about being Abnormal!

 

Team & Work Summary: 

Our Detection team powers our core ML/AI capabilities we leverage to detect and mitigate attacks. You’ll find your work on our Machine Learning team to be at the very center of Abnormal’s success - giving your work incredible impact on our business and customers alike!

Our Detection Engineering team builds the systems that actually detect and mitigate complex, often socially-engineered and adversarial, email-based attacks that target our customers. Composed of a litany of big tech and security veterans alike, this team has created our completely novel and industry disruptive functionality that continues to exceed what customer’s even thought was possible from their email security provider.

 

We’re currently hiring for an experienced mid-level Machine Learning Engineer to initially focus on model efficacy tuning.

To qualify, you’ll need: 

  • To live and work in the US or Canada 
  • A Bachelors or Masters in Computer Science (or similar)
  • To be comfortable working in production quality systems in Python
  • At least 2 Years of end-to-end, production Machine Learning experience within a professional environment
    • We are NOT a Research, Data Science, or Threat Intelligence organization
    • We REQUIRE experience in building end-to-end, production systems

 

Backgrounds/expertise of other successful MLEs at Abnormal:

  • Deep Learning, Natural Language Processing (NLP/NLU), Entity Extraction, 
  • Behavioral ML, like: ranking, recommendation, search, etc.
  • “Serving” Architecture (Yes! Looking at you “Ad Tech” and “Ad Serving” folks!), 
  • Security (or related) domain: Fraud, Abuse, Impersonation, Trust & Safety, Spam, Phishing, Privacy, or similar
  • Anomaly detection, especially on event streaming architectures
  • "Scrappy" E2E MLE experience with rapid-growth/pre-IPO, customer-centric, SaaS startups

 

Why Abnormal?

We’re on a serious mission to “protect the internet” and we’re adamant that building a great team will help us build a great product AND a great company! In addition to ensuring our compensation packages and benefits remain compelling to the caliber of talent we hire - we also seek to provide both clear career and personal growth opportunities. We’ve built a diverse and inclusive team that values the contributions and voice of all team members. Let’s chat about our team and opportunities - we’d love to show you just how GREAT being “Abnormal” can be!

This job is no longer open
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