London - Senior ML Ops Engineer (Experiences)

About this role

About Tripadvisor The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc.

(Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. Tripadvisor Experiences Engineering is the team that builds and supports the world's leading marketplace for travel experiences . We believe that making memories is what travel is all about. And with 400,000+ travel experiences to explore—everything from simple tours to extreme adventures (and everything in between) —making memories that will last a lifetime has never been easier.

This role is a hybrid position based in our London office (minimum 2x per month) open for candidates based in London or maximum 1,5h away from London. What you'll do: Our mission is to make data scientists more productive and to enable broader and deeper utilization of machine learning techniques to help improve business performance. As a Senior ML Ops Engineer, you will play a pivotal role in our dynamic team, collaborating closely with Data Science and Machine Learning experts.

You will have the opportunity to learn many cutting edge technologies around Machine Learning Platform, as also push the boundaries, to test, develop and implement new ideas, technology and opportunities. Your primary responsibilities will include: Empowering Data Science and ML teams, by providing the tools and infrastructure necessary for seamless execution of data science and machine learning tasks. Support tech stack evolution, by developing across our existing technology stack while contributing to our migration into the AWS cloud, leveraging and adopting the latest services available in that environment.

Design, build and maintain a robust and scalable infrastructure to support pre-computed, batch and real-time model needs, ensuring smooth deployment and operation of machine learning models. Foster a culture of innovation by generating and promoting new ideas within the ML Ops domain. Find creative solutions to complex problems, pushing the boundaries of what is possible. What you'll need: 4+ years of ML Ops experience, focused on building modern ML infrastructure catering all stages of a model lifecycle, including development, deployment, management and monitoring.