Abnormal AI · 2 hours ago
Senior Machine Learning Engineer - Attack Detection
United States
Full-time
Remote
Mid, Senior Level
$195K/yr - $230K/yr
4+ years expAbnormal Security is a top cybersecurity startup seeking a Senior Machine Learning Engineer to join their Message Detection Decisioning team. The role involves designing and implementing systems for email detection, improving detection efficacy, and mentoring junior engineers while contributing to the development of a high-precision detection engine.
Artificial Intelligence (AI)Cyber SecurityEmailInformation TechnologyNetwork Security
Responsibilities
Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product
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
Understand features that distinguish safe emails from email attacks, and how our detector stack enables us to catch them
Be the expert in main detection pipelines and decision data flow to be able to drive debugging in systematic degradations caused by bad detectors
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 False Positive rates and efficacy rates for our message detection product attack categories, through feature engineering, rules and ML modeling
Analyze False Negative and False Positive 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
Lead the team’s medium and long term roadmap and drive planning and execution strategy for the pod
Coach and mentor junior engineers to uplevel their code quality and ML effectiveness by providing quality code reviews and design reviews
Participate in building a world-class detection engine across all layers - data quality, feature engineering, model development, experimentation and operation
Qualification
Required
Track record of success in translating business requirements into scalable, maintainable systems with a bias toward simpler but iterative systems
4+ Experience with production ML systems - understands the pillars of a modern ML stack and the development, maintenance and tuning processes of ML models
Uses a systematic approach to debug both data and system issues within ML / heuristics models
Fluent with Python and machine learning libraries like numpy and scikit-learn
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
Independently responsible for the entire lifecycle of projects or features including eng design, development, and deployment
Works well with other stakeholders - has worked with cross-functional teams to drive projects over the finish-line
Machine learning academic background (Bachelor's degree in Computer Science or related fields)
Preferred
MS degree in Computer Science, Electrical Engineering or other related engineering field
Experience with big data or statistics
Familiarity with cyber security industry
Benefits
Bonus
Restricted stock units (RSUs)
Benefits
Company
Abnormal AI
Abnormal AI is the leading AI-native human behavior security platform.
1001-5000 employees
H1B Sponsorship
Abnormal AI has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (5)
Funding
Current Stage
Late StageTotal Funding
$534MKey Investors
Wellington ManagementCrowdStrike Falcon FundInsight Partners
2024-08-06Series D· $250M
2023-03-29Series Unknown
2022-05-10Series C· $210M
Leadership Team
Evan Reiser
Founder & CEO
Sanjay Jeyakumar
CTO, Co-Founder, and Head of R&D
Recent News
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