Detection - Lead NLP Engineer

The Opportunity

Abnormal Security is defining the next generation of email security defense. Spam is a solved problem, and phishing is nearly solved as well. But attackers don’t stop there - they hijack and take over conversations, threaten businesses, impersonate VIPs, send fake invoices, and steal many millions of dollars every year. Here’s where Abnormal Security comes in: we’re laser focused on solving these problems for our customers. Our enterprise customers love us because we consistently detect and stop what everyone else in the market can’t -- advanced attacks that have never been seen before -- and we do so with beautiful user interfaces and best-in-industry customer support.

Our platform uses machine learning and artificial intelligence to baseline communication content, user identity, and behavioral signals in real-time and at-scale in order to detect the abnormalities of email attacks.

You will be a key hire to grow our ML efforts and team and take our ML systems and product to the next level. Over the next two years, Abnormal Security will grow tremendously both in team size, number of customers, and data size. We have a rich dataset and a rich set of problems to tackle, and are in the infancy of building both the platforms and ML models to support a company where ML and detection is a must for its success.

Provide a brief description of the role, what success in the position looks like, and how it fits into the company or organization overall. Explain what this organization and/or team does and how that fits into the overall company goals.

Who you are:

• You have solved complex ML problems, introduced innovative architectures or solutions, and designed end-to-end ML ranking or classification pipelines.
• You have expertise in your area of ML - whether it’s NLP, ranking systems, recommendations, or spam -- and are always looking to learn new areas
• You have worked with and grown other engineers to help them be successful in ML problems

What you’ll do:

• Structuring an ML system that will enable many engineers to make meaningful progress on models that catch e-mails.
• Building systems and models that can quickly learn and adapt to new adversarial attacks.
• Building common ML components (clustering, deep learning models, transfer learning, etc) that can be used to bootstrap and support new product lines.

Experience you’ll need:

• at least 5 years hands-on experience building ML systems
• expertise in one of text understanding, NLP, deep learning, or more
• experience working in the spam, anti-abuse, trust-and-safety, or fraud detection field
• has built end-to-end ML systems including modeling, maintaining production systems, and running experiments
• experience with ML toolkits including sklearn, and pytorch or tensorflow or similar
• experience with big-data processing systems such has spark or hadoop
• strong software engineering and data science skills

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!