Role Description
As a Senior Machine Learning Engineer focused on search quality, you will play a crucial role in developing and enhancing our search capabilities to provide users with the best possible search experience. You will work on designing, coding, training, testing, deploying, and iterating on large-scale machine learning systems that drive the core functionalities of Dropbox Dash’s search features
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
- Contribute to team’s technical strategy for the end-to-end machine learning lifecycle, ensuring alignment with business objectives and driving impactful outcomes
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
- 8+ years of experience in engineering with 5+ years of experience building Machine Learning or AI systems
- Strong industry experience working with large scale data
- Strong collaboration, analytical and problem-solving skills
- Familiarity with the state-of-the-art 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, LangChain, 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
Total Rewards
