Senior Machine Learning Engineer - Remote

Overview

As a Senior Machine Learning Engineer, you will play a key role in advancing Dropbox’s mission to create a more enlightened way of working. Leveraging cutting-edge AI/ML technologies, you will design, build, deploy, and refine large-scale machine learning systems. Your work will power Dropbox Dash’s universal AI search and AI-assisted organization features, transforming how millions of Dropbox users collaborate, stay organized, and focus on the work that truly matters.

In Short

• 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.
• Develop and maintain production-quality code for serving machine learning models at scale.
• Work with Product, Design, Infra structure 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.
• Explore and integrate the latest advancements in Search, LLMs, Recommender Systems, and Representation Learning into Dropbox's products.

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience.
• 8+ years of experience in engineering with 5+ years of experience building Machine Learning or AI systems.
• Professional working experience in ML modeling for at least one of the following: Recommender Systems, Search, or Ranking.
• Strong industry experience working with large scale data.
• Strong collaboration, analytical and problem-solving skills.
• Familiarity with the state-of-the-art in Large Language Models.
• 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, scikit-learn, numpy, pandas, etc.).

Benefits

• Competitive salary and equity packages.
• Comprehensive health benefits.
• Flexible work hours and remote work options.
• Opportunities for professional development and growth.