Vimeo has billions of videos on its platform and millions of people performing searches on that content every month. The Search and Recommendations team surfaces the most relevant content to users, from their own assets to millions of public videos. Powering the very best search experience will require thoughtfulness about the user experience, a lot of data, and cutting edge machine learning. Your task will be to leverage data and algorithms to improve the search experience for our users. You might boost query understanding with NLP, use computer vision techniques to enrich how we index our videos into Elasticsearch, or explore ways to provide personalized search results. The possibilities are endless.
What you’ll do:
- Write clean, portable, and well-documented code
- Work with various machine learning algorithms to boost our search systems’ ability to provide relevant, personalized results in any context
- Gain experience using docker, kubernetes, and Google Cloud technologies for deployments of models
- Iterate on your implementations and designs in a data driven environment
- Gain domain knowledge related to Search by working with experienced search relevance engineers.
- Grow technically by learning from talented full stack engineers
What we’re seeking:
- Some familiarity, interest, and experience with Data Science and Machine Learning (bonus for anything search related, NLP, computer vision, or recommendation systems)
- You have an understanding of Web services and REST APIs
- You are problem-solver who is interested in scale, efficiency, and performance optimization
- You dream big with solutions but also have a strong practical streak in evaluating whether they can and should be implemented
- You’re driven towards projects that have an impact on user experience
- You are familiar with PHP, Python, Go, or Java
- You have strong opinions about how Vimeo search can be improved and are interested in search as a problem
- You have public code viewable on Github, Bitbucket, etc.