Role Description
Responsibilities
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Design, build, evaluate, deploy and iterate on large scale Machine Learning systems
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Understand the Machine Learning stack at Dropbox, and build systems that help Dropbox personalize their users’ experience. Develop and maintain production-quality code for serving machine learning models at scale
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Work with Product, Design, Infrastructure and Frontend teams to bring your models, and features to life
- Contribute to team’s technical strategy for the end-to-end machine learning lifecycle, ensuring alignment with business objectives and driving impactful outcomes
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Explore and integrate the latest advancements in Search, LLMs, Recommender Systems, and Representation Learning into Dropbox's products
Requirements
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BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
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8+ years of experience in engineering with 5+ years of experience building Machine Learning or AI systems
- Strong industry experience working with large scale data
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Strong collaboration, analytical and problem-solving skills
- Familiarity with the state-of-the-art in Large Language Models
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Proven software engineering skills across multiple languages including but not limited to Python, Go, C/C++
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Experience with Machine Learning software tools and libraries (e.g., PyTorch, Scikit-learn, numpy, pandas, etc.)
Preferred Qualifications
- PhD in Computer Science or related field with research in machine learning
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Experience with one or more of the following: Natural Language Processing, Deep Learning, Recommender Systems, Learning to Rank, Speech Processing, Learning from Semi-structured Data, Graph Learning, Large Language Models, and Retrieval-Augmented Generation
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Experience building 0→1 ML products at large (Dropbox-level) scale or multiple 0→1 products at smaller scale including experience with large-scale product systems
Compensation