Machine Learning Engineer

November 20

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Dropbox

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Cloud Storage • Enterprise • Productivity

Dropbox is a cloud-based service that provides tools for storing, sharing, and accessing files across devices. It offers features such as document sharing, video review, automatic backups, and AI-driven scheduling. Dropbox also provides solutions for different sectors like teams, sales, marketing, and education, and industries including construction, media, technology, and manufacturing. With a focus on security, Dropbox ensures files are encrypted and protected against tampering. It offers integrations with various productivity tools and is trusted by major companies for efficient file management and collaboration.

1001 - 5000 employees

Founded 2007

🏢 Enterprise

⚡ Productivity

📋 Description

• Work with large scale data systems, and infrastructure • Help productionize multimodal and semantic retrieval systems at scale, powering Dash’s multimedia and creative search experiences. • Partner with product, design, and infrastructure teams to improve retrieval, ranking, and conversational experiences across image, video, and text content. • Build and iterate on quick prototypes and experimental features, driving innovation in multimodal interaction and creative workflows. • Run quality and performance benchmarks across individual components and end-to-end systems to identify optimization opportunities. • Contribute to open source projects and leverage OSS tools for efficient inference and scaling. • On-call work may be necessary occasionally to help address bugs, outages, or other operational issues.

🎯 Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields • 5+ years of experience in engineering with 3+ years of experience building Machine Learning or AI systems • 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., PyTorch, HuggingFace, TensorFlow, Keras, scikit-learn, etc.) • Familiarity with search-related applications of Large Language Models • Proven experience in machine learning, multimodal AI, or search and ranking systems. • Familiarity with semantic search, embeddings, vector retrieval, and optimizing ranking metrics such as nDCG or MRR.

🏖️ Benefits

• Health insurance • Retirement plans • Professional development opportunities • Flexible work hours