About the Role

Abnormal Security is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection team. 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.  

What you will do 

• Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance.
• Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. 
• Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. 
• Writes code with testability, readability, edge cases, and errors in mind.
• Identify and recommend new features or ML model approaches that can significantly improve detection efficacy for a product
• Train models on well-defined datasets to improve model efficacy on specialized attacks
• Actively monitor and improve FN rates and efficacy rates for our message detection product attack categories, through  feature engineering, rules and ML modeling.
• Analyze FN and FP datasets to categorize capability gaps and recommend short term feature and rule ideas to improve our detection efficacy.

Must Haves 

• Ability to understand business requirements thoroughly and bias toward designing a simplest yet generalizable ML model / system that can accomplish the goal.
• Experience with writing stable and production level pipelines for model training and evaluation leading to reproducible models and metrics.
• Uses a systematic approach to debug both data and system issues within ML / heuristics models.
• Break down tasks, plans, estimates and cuts scope as appropriate to deliver reliably.
• Consistently writes code that is easily testable and understood by other engineers.
• Able to identify risks of an ML project early on to pave a clear path from offline experimentation to production.
• BS degree in Computer Science, Applied Sciences, Information Systems or other related engineering field
• 3+ years experience designing and building machine learning applications

Nice to Have 

• MS degree in Computer Science, Electrical Engineering or other related engineering field
• Experience with big data, statistics and Machine Learning
• Experience with algorithms and optimization
  

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