Machine Learning Engineer II

Job not on LinkedIn

🕒 2 days ago

🇺🇸 United States – Remote

💵 $160.7k - $231k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Abnormal Security

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Abnormal provides total protection against the widest range of attacks including phishing, malware, ransomware, social engineering, executive impersonation, supply chain compromise, internal account compromise, spam, and graymail.

📋 Description

• 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. Work with infrastructure & systems engineers to productionize signals to feed into the detection system. • Writes code with testability, readability, edge cases, and errors in mind. • 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. • Contribute in other areas of the stack: building and debugging data pipelines, or presenting results back to customers in our tools when the occasion arises

🎯 Requirements

• 3+ years experience designing, building and deploying machine learning applications in one of the domains of text understanding, entity recognition, NLP experience, computer vision, recommendation systems, or search. • 1+ years of experience with writing stable and production level pipelines for model training and evaluation leading to reproducible models and metrics. • Experience with data analytics and wielding SQL+pandas+spark framework to both build data and metric generation pipelines, and answer critical questions about system efficacy or counterfactual treatments. • Ability to understand business requirements thoroughly and bias toward designing a simplest yet generalizable ML model / system that can accomplish the goal. • Uses a systematic approach to debug both data and system issues within ML / heuristics models. • Fluent with Python and machine learning toolkits like numpy, sklearn, pytorch and tensorflow. • Effective software engineering skills who can find answers quickly from code base and writes structured, readable, well tested and efficient code. • BS degree in Computer Science, Applied Sciences, Information Systems or other related engineering field

🏖️ Benefits

• Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. • In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.