Senior Machine Learning Engineer

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 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 autonomy 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, Mongo

DB, Postgre

SQL, 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

As a Senior Machine Learning Engineer, you will play a key role in advancing Dropbox’s mission to create a more enlightened way of working. Leveraging cutting‑edge AI/ML technologies, you will design, build, deploy, and refine highly reliable AI agents operating at massive scale. Your work will power Dropbox Dash’s universal agentic search and autonomous organization features, transforming how millions of users collaborate, stay organized, and focus on the work that truly matters.

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 and product ionize agentic AI frameworks — including multi‑agent coordination, planning, tool‑use, and memory — that allow agents to maintain long‑term context and execute complex tasks across the Dropbox ecosystem.
• Lead the end‑to‑end design of ML systems, from fine‑tuning (SFT, RLAIF) and advanced prompting to inference optimization and production monitoring.
• Establish rigorous safety, alignment, and evaluation frameworks to ensure our autonomous systems are helpful, honest, and harmless.
• Collaborate across Product, Design, Infra, and Frontend teams to translate ambiguous user needs into concrete AI capabilities that move the needle for the business.
• Mentor junior engineers and serve as a core contributor to the broader Dropbox AI strategy, fostering a culture of technical excellence.

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

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production‑scale AI/ML systems.
• Professional experience in ML modeling for complex systems…