The Senior Machine Learning Engineer will play a pivotal role in supporting the Threat Intelligence and Product Trust & Safety teams by leveraging advanced machine learning techniques to enhance security, detect and prevent abuse, and protect user trust at Dropbox.
Requirements
- 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 and with systems such as binary and function signals)
- Familiarity with security domains such as phishing detection and account takeover prevention.
- Experience applying machine learning techniques to security-focused problems such as anomaly detection, phishing prevention, and account takeover mitigation.
Responsibilities
- Design, build, and deploy machine learning models to detect and mitigate security threats, such as account takeovers, phishing, and malicious content distribution.
- Develop algorithms for anomaly detection, behavior analysis, and predictive modeling to proactively identify risks and abuse patterns.
- Develop graph, cluster and other adversarial risk signals for detecting and enforcing on bulk and coordinated operation among Dropbox accounts.
- Analyze large, complex datasets from multiple sources, including user behavior, telemetry, and external threat intelligence feeds.
- Develop ML-driven solutions for real-time threat detection and response, including automation of security workflows.
- Partner with data scientists, software engineers, and security analysts to integrate ML models into existing workflows and platforms.
- Collaborate on initiatives to enhance user safety, such as URL reputation scoring, and abuse prevention.
Other
- Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related technical field.
- Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours.
- Strong collaborative skills with cross-functional teams, including data scientists, engineers, and security analysts, to integrate ML solutions into workflows.
- Excellent problem-solving, analytical, and communication skills with a passion for building secure, user-centric solutions.
- Participation in on-call rotations as part of employment
