Machine Learning Engineer at Dropbox
San Francisco, California, United States
🇺🇸 (Posted Jul 3 2018)
About the company
Dropbox is a leading global collaboration platform that's transforming the way people work together, from the smallest business to the largest enterprise. With more than 500 million registered users across more than 180 countries, our mission is to unleash the world’s creative energy by designing a more enlightened way of working. Headquartered in San Francisco, CA, Dropbox has more than 12 offices around the world.
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.
Dropbox’s Machine Learning group develops high impact solutions that touch millions of people and a lot of data. From images to documents in every language, the Dropbox ML team delivers solutions using the full range of ML techniques from computer vision to supervised learning to deep learning to online learning. While some of our algorithms run on mobile devices, others require large clusters on our infrastructure.
Dropbox is looking for Machine Learning Engineers with an academic or practical background in machine learning, ideally with experience in natural language understanding, information retrieval, knowledge extraction, or deep learning.
Work within the Machine Learning Team to design, code, train, test, deploy and iterate on large scale machine learning systems.
Build delightful products and experiences for millions, while working alongside an excellent, cross-functional team across Engineering, Product and Design.
Help shape the direction of machine learning and artificial intelligence at Dropbox.
Skills & requirements
BS and MS in Computer Science or related field with research in machine learning
3+ years of experience building machine learning or AI systems
Strong analytical and problem-solving skills
Solid software engineering skills across multiple languages including but not limited to Python, C/C++
Experience with machine learning software packages (e.g., scikit-learn, TensorFlow, Caffe, Theano, Torch)
Ph.D. 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, reinforcement or active learning, ML software systems, machine learning on mobile devices
Instructions how to apply
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