Machine Learning Engineer

As a Machine Leaning 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.

You will work within the Machine Learning Team to design, code, train, test, deploy and iterate on large scale machine learning systems
You will build delightful products and experiences, while working alongside an excellent, multi-functional team across Engineering, Product and Design
You will help craft the direction of machine learning and artificial intelligence at Dropbox
Develop and maintain production-quality code for serving machine learning models at scale
Design online and offline ML experiments, perform data analysis, and explore feature quality for ML models
Communicate technical trade-offs to multidisciplinary stakeholders, including product managers, software developers, and business leaders
Proactively explore and integrate the latest advancements in Machine Learning into Dropbox's products

BS, MS, or PhD in Computer Science or related technical field involving Machine Learning, or equivalent technical experience
5+ years of experience building production search or recommendation machine learning systems
Proven software engineering skills across multiple languages including but not limited to Python and Go
Familiarity with scalable search systems(e.g. ElasticSearch, OpenSearch, Lucene) and information retrieval algorithms(e.g. TF-IDF, BM25, Learning to Rank)
Experience with machine learning software packages(e.g., scikit-learn, TensorFlow, PyTorch), and related libraries(numpy, pandas)
Experience designing high-impact features for search or recommendation systems and developing, supporting, and debugging feature generation ETL pipelines
Strong analytical, problem-solving, and communication skills