Senior Machine Learning Software Engineer

Sorry, this job was removed at 02:44 p.m. (PST) on Friday, Oct 18, 2024
Remote
Internship
Cloud • Consumer Web • Productivity • Software • App development • Automation • Data Privacy
Our mission is to design a more enlightened way of working. Join us!
The Role

Role Description

Dropbox is looking for a Machine Learning Engineer to join our User Understanding team. User Understanding team’s mission is to personalize users’ journey through Dropbox products and features. The team 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
  • 5+ years of experience 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

What the Team is Saying

Caitlin
Latane
Drew
Mack
The Company
San Francisco, CA
2,500 Employees
Remote Workplace
Year Founded: 2007

What We Do

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.

Why Work With Us

Our remote work model is a deliberate shift to provide greater flexibility, create a level-playing field, and evolve our culture to focus on people over places. Being a Virtual First company has allowed us to focus on our impact and effectiveness, by making investments in our employees according to what they need to do their best work.

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Dropbox Offices

Remote Workspace

Employees work remotely.

While remote work is the primary experience for our employees, we also prioritize opportunities for quarterly in-person collaboration knowing that connection is vital to a thriving workforce. We focus on how we work, not where we work.

Typical time on-site: None
San Francisco, CA

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