Senior Machine Learning Engineer, Strategic Intelligence Group

Company Description

Dropbox isn’t just a workplace—it’s a living lab for more enlightened ways of working. We're a global community of more than 2,000 bold visionaries and resourceful doers who are shaping the future of Dropbox—and with it the future of work. Our Virtual First model combines the flexibility of a distributed workplace with the power of human connection, making space for both meaningful work and meaningful relationships. With our start-up mindset and enterprise-level opportunities, you can be who you are and grow into who you’re meant to be. Here, you can own your impact to make work more intuitive, joyful, and human—for you as a Dropboxer and for hundreds of millions of people worldwide. If you're ready to push boundaries—and yourself— Dropbox is ready for you.

Team Description

The Dropbox Engineering Team builds the technology that creates more enlightened ways of working for hundreds of millions of people. Every day, our platforms—including Dropbox Dash, Dropbox Sign, and our core sync engine—handle over a billion files for users worldwide, creating engineering challenges as great as the opportunity for impact. Our software engineering team uses a range of technologies to solve interesting problems, including Python, React, Node.js, JavaScript, MongoDB, PostgreSQL, and Android development. We think like a startup but build for an enterprise, exploring new possibilities that transform how people work. If you're excited about turning complex technical challenges into intuitive solutions at scale, join our Engineering team. Areas of work include Machine Learning Engineers, Infrastructure Engineer, Product SWE Frontend and Backend, Mobile Software Engineers (iOS and Android), Engineering Manager, Data Engineer, Software Development Engineer in Test, Security Engineering, Site Reliability Engineer, Technical Program Managers, Network Engineer, Datacenter Engineer, Technical Supply Chain Manager and more.

Role Description

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. This role involves designing, implementing, and maintaining ML models and systems to identify threats, analyze behavioral patterns, and mitigate platform abuse. The ideal candidate has a strong foundation in machine learning, data science, and software engineering, with a passion for security and product trust.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

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.
• Work closely with Threat Intelligence, Product Trust & Safety, and Security Engineering teams to define and prioritize ML projects aligned with organizational goals.
• Partner with data scientists, software engineers, and security analysts to integrate ML models into existing workflows and platforms.
• 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.
• Collaborate on initiatives to enhance user safety, such as URL reputation scoring, and abuse prevention.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

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 and with systems such as  binary and function signals)
• Familiarity with security domains such as phishing detection and account takeover prevention

Preferred Qualifications

• Experience applying machine learning techniques to security-focused problems such as anomaly detection, phishing prevention, and account takeover mitigation
• Strong understanding of ML algorithms for behavior analysis, predictive modeling, and real-time threat detection
• Strong collaborative skills with cross-functional teams, including data scientists, engineers, and security analysts, to integrate ML solutions into workflows
• Demonstrated ability to design, deploy, and optimize production-level ML systems in high-impact areas
• Excellent problem-solving, analytical, and communication skills with a passion for building secure, user-centric solutions

Compensation

Dropbox is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work.