Vimeo empowers video creators to tell exceptional stories and connect with their audiences and communities. Home to more than 60 million members in over 150 countries, Vimeo is the world’s largest ad-free open video platform and provides powerful tools to host, share and sell videos in the highest quality possible.
The Machine Learning Research team at Vimeo is focused on developing, deploying, and maintaining machine learning models to help support and enhance the capabilities of various teams across Vimeo. Whether it's targeting users for marketing, improving quality-of-experience in playback, or enabling visual classification of all videos at Vimeo, the Machine Learning Research team has a wide selection of projects in its future. By applying open source solutions, or experimenting with creating our own, we're focused on deploying the latest and greatest in ML across the stack.
What you’ll do:
- Contribute to building, iterating, evaluating, and shipping machine learning models
- Develop monitoring and tooling for machine learning systems
- Help build pipelines and APIs for offline and online inference
- Gain experience using docker, Kubernetes, and Google Cloud technologies for MLOps and model lifecycle management
- Work with other teams to understand real problems and develop strategies to improve or entirely solve problems with machine learning
- Write clean, portable, and well-documented code
What we’re seeking:
- You are currently pursuing a B.S. or M.S./Ph.D in Machine Learning, Computer Science, Software Engineering, or related technical field, with an expected graduation date of 2021 or 2022
- You have experience working with any of these languages: Python, Go, Java, C++
- You are familiar with machine learning libraries or frameworks such as sklearn, keras, tensorflow, pytorch, spark-ml, R
- You have experience in ML engineering, through previous internships, coursework or open-source projects
- You are passionate about designing software systems and shipping high-quality code
- You are familiar with DevOps cloud tools (AWS/EC2, or Google Cloud) or MLOps tools (Kubeflow)
This is a paid internship.
While we offer competitive compensation, we don't provide accommodation. Please ensure you are interested in an internship in New York City under these circumstances before applying.