Machine Learning Engineer II
Abnormal SecurityEmail Security company
United StatesSenior
Wellington Management
Greylock Partners
Menlo Ventures
Insight Partners
CrowdStrike Falcon Fund
Data & AI
About the role
TL;DR
Join Abnormal Security's Attack Detection team as a Machine Learning Engineer II.
- •Abnormal AI is looking for a Machine Learning 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.
- •Key Responsibilities 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.
- •Identify and recommend new features groups 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.
- •Analyze FN and FP datasets to categorize capability gaps and recommend short term feature and rule ideas to improve our detection efficacy.
- •Requirements 3+ years experience designing, building and deploying machine learning applications. 1+ years of experience with writing stable and production level pipelines for model training and evaluation.
- •Experience with data analytics and wielding SQL+pandas+spark framework.
- •Fluent with Python and machine learning toolkits like numpy, sklearn, pytorch and tensorflow.
- •BS degree in Computer Science, Applied Sciences, Information Systems or other related engineering field.
Required skills
PythonSQLPandasNumPyTensorFlowPyTorchscikit-learn
Domain expertise
cybersecurity
Tech stack
PythonSQLPandasNumPyTensorFlowPyTorchscikit-learn