Role Description

Dropbox is looking for a Senior Machine Learning Engineer. A Machine Learning engineer develops models, systems and features that leverage the massive scale of Dropbox’s user base to understand and predict user behavior to optimize the experience at all stages of the user journey at Dropbox. Relevant experience can range from working on a wide-variety of optimization, and classification problems, e.g. segmentation, propensity modeling, text/sentiment classification, click-through rate prediction, collaborative filtering/recommendation, or spam detection.

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, Infra 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

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
• 8+ years of engineering experience with 3+ years building Machine Learning or AI systems
• Strong industry experience working with large scale data
• Strong analytical and problem-solving skills
• 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., Scikit-learn, TensorFlow, Keras, PyTorch, 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, recommendation systems, learning for search, speech processing, learning from semistructured data, graph learning, reinforcement or active learning, ML software systems, machine learning on mobile devices

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.

Total Rewards 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.

For candidates hired in San Francisco metro, New York City metro, or Seattle metro, the expected salary/On-Target Earnings (OTE) range for the role is currently $206,600 - $243,000 - $279,500. 

For candidates hired in the following locations: 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 (outside Seattle metro) and Washington DC metro, the expected salary/On-Target Earnings (OTE) range for the role is currently $185,900 - $218,700 - $251,500. 

For candidates hired in all other US locations, the expected salary/On-Target Earnings (OTE) range for this role is currently $165,200 - $194,400 - $223,600. 

Range(s) is subject to change. 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. Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use. 

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).