Detection Machine Learning Manager

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2 days ago

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Abnormal Security

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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.

501 - 1000 employees

📋 Description

• Own the execution success of the quarterly roadmap for the Attack Detection team; engage continuously with the Tech Leads to help adjust and prioritize current roadmap items according to the team’s charter and company priorities. • Deliver on: • Extremely high recall detector engine in an adversarial environment using model based as well as heuristic detectors. • Automated model retraining pipelines based continuous ML deployment system to automatically ‘learn’ from new patterns. • Text based signal models to capture and model suspiciousness of email content in multiple languages. • Own both directly customer impacting metrics and system metrics and able to work with the team to proactively identify new attacks and repair degradations: • Recall ie False Negative metrics for our customer base across various attack types. • Overall attack and precision metrics for highly flagging generalized ML models. • Automation metrics for responses to customer specific requirements • Own the machine learning feature consumption layer for both message metadata/content and current/historical user behavior type of signals and and systems and processes to continuously incorporate new features types into existing and new ML models. • Drive processes to enable the team to deliver on projects that are set by TLs as part of the technical roadmap. • Manage the quarterly roadmap updates, project time estimates, weekly sprint planning, day-to-day standups • Identify risks on project delivery (technical, operational, dependency risks) and escalate to appropriate technical leads • Able to assess progress in a metrics-oriented manner • Provide continuous feedback • Responsible for mentoring and growing the engineers on the team by providing constructive feedback at regular intervals to help them successfully execute high impact projects. • Drive Stakeholder alignment : Collaborate with the platform and infrastructure initiatives on company wide initiatives to help increase efficiency, customer adoption and engineer effectiveness goals.

🎯 Requirements

• 2+ years experience of managing data driven (ML) product teams running at large scale data ( 100M+ ) and ability to guide a team technically in this respect. • 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. • 4+ years of hands-on experience in building and safely shipping backend heavy product ML adjacent systems at high velocity. • Ability to understand business requirements thoroughly and bias toward guiding the team to build a simplest yet generalizable ML model / system that can accomplish the goal. • Metrics driven culture: Has led a team of engineers in building out systems and displayed the ability to define metrics of excellence and setup processes to continuously monitor and maintain high standards on metrics. • Be Customer obsessed: Worked with multiple stakeholders to gather requirements and then prioritize and balance against the team's roadmap. • Set High standards - sets high standards and expectations for project execution for themselves and the whole team.

🏖️ Benefits

• Bonus eligibility • Restricted stock units (RSUs) • Benefits