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

• 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 such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

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 such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Preferred Qualifications

• PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
• Proven track record of taking AI products from concept to launch, either at a massive scale (millions of users) or by leading multiple 0 → 1 cycles in a fast-paced environment.
• Hands-on experience with autonomous agent frameworks, multi-step planning, tool-use (function calling), and advanced RAG.
• Experience with inference optimization, model distillation, or fine-tuning techniques to improve performance and cost-efficiency.

Compensation

US Zone 1

$245,200—$331,800 USD

US Zone 2

$220,700—$298,700 USD

US Zone 3

$196,200—$265,400 USD

• US Zone 1: San Francisco metro, New York City metro, or Seattle metro
• US Zone 2: California (outside SF metro), Colorado, Connecticut (outside NYC metro), Delaware, Illinois (Chicago metro), Indiana (Chicago metro), Maryland, Massachusetts, Michigan (Chicago metro), New Hampshire, New Jersey (outside NYC metro), New York (outside NYC metro), Oregon, Pennsylvania (D.C. metro), Pennsylvania (outside NYC metro), Texas (Austin metro) Virginia (DC metro), Washington (outside Seattle metro), Washington DC metro, West Virginia (DC metro), Wisconsin (Chicago metro)
• US Zone 3: All other US locations

Dropbox is a Virtual First company and is open to hiring candidates in all authorized locations.

Company Description

Dropbox isn’t just a workplace—it’s a living lab for designing a more enlightened way of working. We’re a global community of bold visionaries and resourceful doers shaping the future of Dropbox and, in turn, the future of work. Our Virtual First model combines the autonomy of a distributed workplace with the power of human connection, creating space for meaningful work and lasting relationships. With a startup mindset and enterprise-level opportunities, we expect Dropbox employees to think critically, stay curious, and use modern tools, including AI, to improve how work gets done. Here, you can be who you are and grow into who you’re meant to be. You own your impact, helping make work more intuitive, joyful, and human for yourself and hundreds of millions of people worldwide. If you’re ready to push boundaries and challenge yourself, Dropbox is ready for you.

Team Description

The Dropbox Engineering Team develops the technology, platforms, and products that create more enlightened ways of working for hundreds of millions of people. Customers rely on Dropbox to manage, share, and collaborate on content seamlessly—our engineering makes that easier and more intuitive than ever before.Our platform features a robust systems software layer that stores and processes exabytes of data, and a suite of growing services that enhance core products like our sharing and sync engine. We’re also driving innovation with new offerings such as Dash, our AI-powered knowledge management engine. Our infrastructure spans high-performance servers and cutting-edge components across multiple data centers worldwide, ensuring reliability, speed, and scalability at a global scale. 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.

Virtual First

Dropbox’s Virtual First way of working is designed to help people do their best work with flexibility, autonomy, and connection. Day to day, teams work remotely with nonlinear schedules and core collaboration hours that support deep focus and individual working styles. We prioritize asynchronous communication to improve clarity, respect deep work time, and reduce unnecessary meetings. While remote work is the primary experience for our employees, we also prioritize intentional, in-person connection. We bring teams together through regular team gatherings, on-demand workspaces, and Dropbox Neighborhood events in order to strengthen team cohesion, foster creativity, and enhance momentum. Virtual First is built to provide the same access to opportunity, growth, and impact for everyone, regardless of location.

This role requires travel to offsites and various other team gatherings (approximately 5-10% of the year or 2-3 days per quarter). We provide advance notice when possible and encourage candidates to discuss any accommodation needs during the interview process.

Dropbox supports responsible use of AI for preparation, but misrepresentation of skills or experience is not permitted. See our AI Principles.

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.