Dropbox is a special place where we are all seeking to fulfill our mission to design a more enlightened way of working. We’re looking for innovative talent to join us on our journey. The words shared by our founders at the start of Dropbox still ring true today. Wouldn’t it be great if our working environment—and the tools we use—were designed with people’s actual needs in mind? Imagine if every minute at work were well spent—if we could focus and spend our time on the things that matter. This is possible, and Dropbox is connecting the dots. The nearly 3,000 Dropboxers around the world have helped make Dropbox a living workspace – the place where people come together and their ideas come to life. Our 700+ million global users have been some of our best salespeople, and they have helped us acquire customers with incredible efficiency. As a result, we reached a billion dollar revenue run rate faster than any software-as-a-service company in history. Dropbox is making the dream of a fulfilling and seamless work life a reality. We hope you’ll join us on the journey.
Team Description
Our Engineering team is working to simplify the way people work together. They’re building a family of products that handle over a billion files a day for people around the world. With our broad mission and massive scale, there are countless opportunities to make an impact.
Role Description
As a Machine Leaning Engineer, you will be involved in shaping the future direction of the organization and pushing the boundaries on what the world thinks is possible by leveraging the latest advancements in AI/ML. You will join a team of top-tier Machine Learning Engineers and be an inherent part of the product org to create and build delightful new experiences.
Collaborating closely with cross-functional teams, you’ll leverage your ML expertise to tackle audacious challenges. Your contributions will directly impact millions of users, as every line of code you write furthers our mission to revolutionize the way people work and collaborate.
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, evaluate, deploy and iterate on large scale Machine Learning systems
- Understand the Machine Learning stack at Dropbox, and build systems that help Dropbox personalize their users’ experience
- Work with Product, Design, Infrastructure and Frontend teams to bring your models, and features to life
- Work with large scale data systems, and infrastructure
- Evaluate the performance of machine learning systems against business objectives, and productionize those models
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 other quantitative fields or related work experience
- 5+ years of experience in engineering with 3+ years of experience building Machine Learning or AI systems
- Strong industry experience working with large scale data
- Strong analytical and problem-solving skills
- Familiarity with search-related applications of Large Language Models
- Proven software engineering skills across multiple languages including but not limited to Python, Go, C/C++
- Experience with Machine Learning software tools and libraries (e.g., PyTorch, HuggingFace, TensorFlow, Keras, Scikit-learn, etc.)
Preferred Qualifications
- PhD in Computer Science or related field with research in machine learning
- Experience with one or more of the following: natural language processing, deep learning, bayesian reasoning, recommender systems, learning to rank, speech processing, learning from semistructured data, graph learning, reinforcement or active learning, large language models, ML software systems, retrieval-augmented generation, machine learning on edge devices
Compensation
The range(s) listed above is the expected annual salary/OTE (On-Target Earnings) for this role, subject to change.
Please note, OTE are for sales roles only.
Salary/OTE is just one component of Dropbox’s total rewards package. All regular employees are also eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).
Dropbox takes a number of factors into account when determining individual starting pay, including job and level they are hired into, location/metropolitan area, skillset, and peer compensation. We target most new hire offers between the minimum up to the middle of the range.
Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use. Current US Zone locations are as follows:
• US Zone 1: San Francisco metro, New York City metro, or Seattle metro
• US Zone 2: Austin (TX) metro, Chicago metro, California (outside SF metro), Colorado, Connecticut (outside NYC metro), Delaware, Massachusetts, New Hampshire, New York (outside NYC metro), Oregon, Pennsylvania (outside NYC or DC metro), Washington DC metro, and West Virginia (DC metro)
• US Zone 3: All other US locations
Dropbox is a Virtual First company and is open to hiring candidates in all authorized locations.