As a Machine Leaning Engineer on our Multimedia AI team, you will be involved in shaping the future direction of Dropbox Dash and pushing the boundaries on what the world thinks is possible by leveraging the latest advancements in AI/ML. You will join a team of top-tier Machine Learning Engineers and be an inherent part of the product org to create and build delightful new experiences.
Collaborating closely with cross-functional teams, you'll leverage your ML expertise to tackle audacious challenges. Your contributions will directly impact millions of users, as every line of code you write furthers our mission to revolutionize the way people work and collaborate.
Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.
- 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, with the goal of maintaining a stable and high-quality experience for our customers.
Requirements- BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
- 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.
- Experience running quality and performance benchmarks across components and end-to-end pipelines in large-scale machine learning and retrieval systems to identify and drive optimizations.
- PhD 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, recommender systems, learning to rank, speech processing, learning from semistructured data, graph learning, reinforcement or active learning, large language models, ML software systems, retrieval-augmented generation, machine learning on edge devices
- 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
Top Skills
What the Team is Saying
What We Do
We're a global community of bold visionaries and resourceful doers who are shaping the future of Dropbox—and with it the future of work. Our Virtual First model combines the flexibility of a distributed workplace with the power of human connection, making space for both meaningful work and meaningful relationships. With our start-up mindset and enterprise-level opportunities, you can be who you are and grow into who you’re meant to be. Here, you can own your impact to make work more intuitive, joyful, and human—for you as a Dropboxer and for hundreds of millions of people worldwide. If you're ready to push boundaries—and yourself—Dropbox is ready for you.
Why Work With Us
We believe people do their best work when empowered with autonomy and harmony, and we understand there’s no substitute for human connection. Our Virtual First model combines the flexibility of remote work with the power of in-person collaboration to create the best of both worlds: a distributed workplace, anchored in community.
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Employees work remotely.
While remote work is the primary experience for our employees, we also prioritize opportunities for quarterly in-person collaboration knowing that connection is vital to a thriving workforce. We focus on how we work, not where we work.
