Dropbox
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Senior Machine Learning Software Engineer

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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
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What are Dropbox Perks + Benefits

Dropbox Benefits Overview

We’re proud to offer benefits that help all Dropboxers take care of their holistic selves, so they can keep flowing at work.

Culture
Volunteer in local community
Partners with nonprofits
Open door policy
OKR operational model
Team based strategic planning
Pair programming
Employee resource groups
Employee-led culture committees
Flexible work schedule
Remote work program
Diversity
Documented equal pay policy
Dedicated diversity and inclusion staff
Mandated unconscious bias training
Diversity manifesto
Diversity employee resource groups
Hiring practices that promote diversity
Health Insurance + Wellness
Flexible Spending Account (FSA)
Disability insurance
Dental insurance
Vision insurance
Health insurance
Life insurance
Wellness programs
Team workouts
Mental health benefits
Financial & Retirement
401(K)
401(K) matching
Company equity
Performance bonus
Charitable contribution matching
Child Care & Parental Leave
Childcare benefits
Generous parental leave
Family medical leave
Adoption Assistance
Restricted work hours
Return-to-work program post parental leave
Vacation + Time Off
Unlimited vacation policy
Generous PTO
Paid volunteer time
Sabbatical
At Dropbox, this is called 'Recharge'
Paid holidays
Office Perks
Company-sponsored outings
Free snacks and drinks
Some meals provided
Company-sponsored happy hours
Recreational clubs
Relocation assistance
Fitness stipend
Home-office stipend for remote employees
Professional Development
Job training & conferences
Tuition reimbursement
Lunch and learns
Promote from within
Mentorship program
Continuing education stipend
Continuing education available during work hours
Online course subscriptions available
Customized development tracks

Additional Perks + Benefits

In order to be successful in our Virtual First environment we needed to make changes that would allow employees to have more control over both where and how they work. Therefore, we embrace “non-linear workdays” with defined core collaboration hours that overlap across time zones. Beyond that, we encourage employees to design their own schedules to balance collaboration with needs for individual focus. We’ve also moved from “all day syncs” to an “async by default” culture, reserving meetings for discussion, debate, and decision-making, and handling all other work in our deep focus hours.

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