About This Role
About the Team
As a member of the summarization team, you will advance state of the art text summarization, collaborate with expert industry partners on both hardware and models, and ultimately develop and maintain production systems that benefit hundreds millions of users!
About the Role
Help develop state-of-the-art abstractive text summarization systems using large language models (LLMs)
Manage data ingestion processes, oversee labeling efforts and monitor data quality to support your own machine learning models.
Proactively identify model failure cases and identify new approaches for improving our machine learning models.
Continued education about the latest machine learning algorithms, techniques, and technologies.
5+ years of professional experience as an ML Engineer (2+ with PhD)
Professional or extensive academic experience with text summarization
BS & MS in Computer Science or related field, PhD preferred
Ability to leverage large-scale compute resources, including distributed GPUs, to train and evaluate very large neural networks.
Familiarity with advanced models such as BERT
Working knowledge of machine learning techniques and algorithms, ranging from logistic regression to deep neural networks.
Professional experience with basic NLP, including techniques such as tokenization, lemmatization, and TF-IDF vectorization.
Ability to manage datasets and evaluate ML model performance, using train/test splits, cross-validation, and task-specific metrics.
Proficiency in Python, including basic skills such as setting up virtual environments, installing packages from PyPI, and debugging common problems using online resources.
Ability to create large software projects that are organized, well-structured, thoughtfully documented, and automatically tested.
Experience deploying machine learning models to production.
Nice to Have
Proven record of working with open-source communities.
Familiarity with web frameworks such as Flask, Tornado, Starlette, or FastAPI.
Salary Range or On Target Earnings:
In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.
Information about Zoom’s benefits is on our careers page here.
Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.
We also have a location based compensation structure; there may be a different range for candidates in this and other locations.
Work Styles at Zoom
In most cases, you will have the opportunity to choose your preferred working location from the following options when you join Zoom: in-person, hybrid or remote. Visit this page for more information about Zoom's Workstyles.
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