Dropbox
Dropbox is a cloud-based service that provides tools for storing, sharing, and accessing files across devices. It offers features such as document sharing, video review, automatic backups, and AI-driven scheduling. Dropbox also provides solutions for different sectors like teams, sales, marketing, and education, and industries including construction, media, technology, and manufacturing. With a focus on security, Dropbox ensures files are encrypted and protected against tampering. It offers integrations with various productivity tools and is trusted by major companies for efficient file management and collaboration.
Cross-platform file sync • File sharing • Online backup • Cloud storage • Collaboration
Senior Machine Learning Engineer
January 28
Dropbox
Dropbox is a cloud-based service that provides tools for storing, sharing, and accessing files across devices. It offers features such as document sharing, video review, automatic backups, and AI-driven scheduling. Dropbox also provides solutions for different sectors like teams, sales, marketing, and education, and industries including construction, media, technology, and manufacturing. With a focus on security, Dropbox ensures files are encrypted and protected against tampering. It offers integrations with various productivity tools and is trusted by major companies for efficient file management and collaboration.
Cross-platform file sync • File sharing • Online backup • Cloud storage • Collaboration
📋 Description
• The Senior Machine Learning Engineer will play a pivotal role in supporting the Threat Intelligence and Product Trust & Safety teams. • This role involves designing, implementing, and maintaining ML models and systems to identify threats, analyze behavioral patterns, and mitigate platform abuse.
🎯 Requirements
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related technical field • 8+ Years experience designing, building, and deploying ML models for security-related use cases such as anomaly detection, behavior analysis, predictive modeling, and adversarial threat detection • Experience developing ML-driven real-time detection systems using tools like Apache Kafka, AWS Kinesis, or Google Pub/Sub • Proficiency with graph-based ML models, clustering techniques, and graph neural networks (GNNs) for detecting coordinated malicious activities • Proficiency in Python, Scala, or Java for developing and deploying ML solutions • Familiarity with scalable data systems (e.g. Databricks, Spark, data lakes) • Familiarity with security domains such as phishing detection and account takeover prevention
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