At Booking.com, data drives our decisions. Technology is at our core and innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you make. The journeys you take. The sights you see. And the food you sample. Through our products, partners and people, we can empower everyone to experience the world.
The Content Intelligence team builds the Content Intelligence Platform by consuming millions of images and textual inputs every day, and then enriching it with ML capabilities. Eventually, these will serve downstream applications and personalize our customers' experience (think of a way to choose and surface the right images and reviews when customers book their next vacation).Moreover the team is taking a key role in building in-house LLMs for different needs as: moderation, translation, AI trip planner chatbot, content generation and other GenAI applications.
About the role:As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models. You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
Key Job Responsibilities and Duties:- Explore and apply state-of-the-art techniques in multimodal machine learning.
- Train innovative ML models (NLP, CV, LLM-finetuning…), build algorithms, and engineering approaches to drive business impact.
- Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
- Conduct data analysis with detailed metrics to evaluate model’s performance, labels quality, features exploration.
- Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
- Collaborate with multidisciplinary teams: product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.
- Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and GenerativeAI models at scale.
- Experience designing and executing end-to‑end research and development plans and generating impact through large‑scale machine learning model development. Preferably evidenced by peer‑reviewed publication, patents, open sourced code or the like.
- Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience), involved in the application of Machine Learning to business problems.
- Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
- Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
- Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
- Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
- Excellent English communication skills, both written and verbal.
- Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels.
- Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators.
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique‑to‑Booking.com benefits which include:
- Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave.
- Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country).
- Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit.
Inclusion has been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations.
Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and inclusive travel experience for everyone. Inclusion is at the heart of everything we do. It’s a place where you can make your mark and have a real impact in travel and tech.”
We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment.
Application Process:- Let’s go places together: How we Hire.
- This role does not come with relocation assistance.
Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive.
Pre-Employment ScreeningIf your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.
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