Senior Machine Learning Software Engineer, New Initiatives

Role Description
At Dropbox, our pursuit of excellence in Machine Learning and Artificial Intelligence fuels our mission to empower users worldwide. We've cultivated a culture rooted in meticulous attention to detail, unwavering commitment to reliability, and a drive to innovate at scale.

As a Senior Machine Leaning Engineer, you will be involved in shaping the future direction of the organization 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.

Responsibilities

• 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
• Work with Product, Design, Infra and Frontend teams to bring your models, and features to life
• Work with large scale data systems, and infrastructure
• Evaluate the performance of machine learning systems against business objectives, and productionize those models
• Contribute to team’s technical strategy for the end-to-end machine learning lifecycle, ensuring alignment with business objectives and driving impactful outcomes

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
• 8+ years of engineering experience with 5+ years building Machine Learning or AI systems
• Strong industry experience working with large scale data
• Strong collaboration, analytical and problem-solving skills
• 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., Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace, LangChain etc.)

• 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