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Job Location: San Francisco, CA
Work Styles at Zoom
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About Us
Zoomies help people stay connected so they can get more done together. We set out to build the best video product for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.
We’re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Here, you’ll work across teams to deliver impactful projects that are changing the way people communicate and enjoy opportunities to advance your career in a diverse, inclusive environment.
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!
The Skill Set
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5+ years of professional experience as an ML Engineer (2+ with PhD)
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Professional or extensive academic experience with text summarization
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BS & MS in Computer Science or related field
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Ability to leverage large-scale compute resources, including distributed GPUs, to train and evaluate very large neural networks.
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Familiarity with advanced models such as BERT
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Working knowledge of machine learning techniques and algorithms, ranging from logistic regression to deep neural networks.
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Professional experience with basic NLP, including techniques such as tokenization, lemmatization, and TF-IDF vectorization.
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Ability to manage datasets and evaluate ML model performance, using train/test splits, cross-validation, and task-specific metrics.
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Proficiency in Python, including basic skills such as setting up virtual environments, installing packages from PyPI, and debugging common problems using online resources.
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Ability to create large software projects that are organized, well-structured, thoughtfully documented, and automatically tested.
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Experience deploying machine learning models to production.
Nice to Have
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Proven record of working with open-source communities.
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Familiarity with web frameworks such as Flask, Tornado, Starlette, or FastAPI.
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Experience with server-side JavaScript or TypeScript, including comfort with tools such as npm.
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PhD in Computer Science or related field
What You’ll Do
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Help develop state-of-the-art abstractive text summarization systems using large language models (LLMs)
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Manage data ingestion processes, oversee labeling efforts and monitor data quality to support your own machine learning models.
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Proactively identify model failure cases and identify new approaches for improving our machine learning models.
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Continued education about the latest machine learning algorithms, techniques, and technologies.
We believe that the unique contributions of all Zoomies is the driver of our success. To make sure that our products and culture continue to incorporate everyone’s perspectives and experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Zoom is proud to be an equal opportunity workplace and is an affirmative action employer. All your information will be kept confidential according to EEO guidelines.
We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law. If you need any assistance or accommodations due to a medical condition, or if you need assistance accessing our website or completing the application process, please let us know by emailing us at
careers@zoom.us
.
At Zoom, we care about our employees, their families, and their well-being. As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways.
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