|Published||December 12, 2022|
|Location||London, United Kingdom|
We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique identities, abilities, and experiences, so we can collectively revolutionize travel and together find the good out there.
About the Role
This role is to be based remotely or hybrid in Portugal only, you have to be living in Portugal to work remotely.
The Tripadvisor Data Science Team is looking for an exceptional individual to help design and build next generation systems that model how travelers interact with the various products on the site. Such models will allow a significant improvement in our ability to offer to travelers the most tailored and relevant travel products to them (e.g. showing the top family-friendly beachfront properties in Cancun). This individual will have the opportunity to work on deep learning projects across a variety of verticals including hotels, restaurants, experiences, etc. with a strong focus on computer vision, and work on problems including (but not limited to) image understanding, sorting and recommendation, content moderation, etc.
Tripadvisor is the web's leading travel information site. At Tripadvisor, the Data Science Team creates systems that influence the travel decisions of millions of people per day. It applies cutting edge machine learning techniques to a wide variety of areas, including sorting, recommendation, computer vision, natural language processing, etc. To ensure continued success, Tripadvisor promotes a culture of personal development, including social activities, journal clubs, memberships in online learning resources, and participation in industry conferences. Have a great time while shaping the future of travel!
Who you are:
You are an altruistic team player, who gets things done and loves to learn – you thrive on communicating well but are also comfortable working independently across multiple projects.
What you will be doing:
- Implementing cutting edge machine learning models in image classification, object detection, semantic segmentation, etc., to solve a variety of core business problems
- Harnessing our database of over 600M images to train new models
- Writing ETL automation pipelines
- Building prototypes, running evaluations, optimizing deployments, and maintaining new models in production
- Designing A/B tests and analyzing their results
- Communicating progress and experimental results to technical and business stakeholders
- Planning and brainstorming future projects
- Advanced degree in Computer Science, Data Science, Engineering, Statistics, or related field
- 2+ years experience developing deep learning models at scale from inception to production
- Strong background in machine learning, deep learning, and statistics
- Strong computer science (data structures and algorithms) foundation
- Proficiency in a mainstream Python deep learning framework: PyTorch, Tensorflow, or Keras
- Experience with big data technologies, such as Snowflake, Hive, Spark, etc. and ability to write complex SQL queries
- Experience with modern python based data science libraries including pandas, numpy, scikit-learn, and tools like Jupyter notebooks, etc.
- 3+ years experience developing deep learning models at scale from inception to production; and, at least one year of industrial experience with computer vision models
- Experience with hosted notebooks and modern ML tooling: Kubeflow, MLflow, W&B, etc.
- Knowledge of A/B test design and analysis
- Experience doing ML & data science for large scale online services
What you’ll get:
Highly competitive salary along with the following:
- Annual bonus
- Stock options
- Excellent contributory pension
- Full family private medical cover
- Full dental cover
- Annual wellbeing allowance (e.g. gym membership, Apple Watch, etc.)
- Complimentary Tripadvisor Plus membership
- Personal travel reimbursement and other travel discounts
- Critical illness plus full life cover
- Employee assistance program