Machine Learning Engineer
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.
- BS and MS in Computer Science or related field with research in machine learning
- 5+ 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
Benefits and Perks
- 100% company paid individual medical, dental, & vision insurance coverage
- 401k + company match
- Market competitive total compensation package
- Free Dropbox space for your friends and family
- Wellness Reimbursement
- Generous vacation policy
- 10 company paid holidays
- Volunteer time off
- Company sponsored tech talks (technology and other relevant professional topics)
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