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Role Description
As a 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.
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.
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, Infrastructure 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
Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.
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
- Strong industry experience working with large scale data
- Strong analytical and problem-solving skills
- Familiarity with search-related applications of 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, HuggingFace, TensorFlow, Keras, Scikit-learn, etc.)
Preferred Qualifications
- 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
Compensation
US Zone 1
$204,000—$276,000 USD
US Zone 2
$183,500—$248,400 USD
US Zone 3
$163,000—$220,800 USD
Dropbox Seattle, Washington, USA Office
Though remote is our primary way of working, meaningful in-person connection and collaboration is a critical part of Virtual First. Our Seattle Studio is a place for teams to come together to host meetings, off-sites, and build community.
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