Machine Learning Scientist II - Content Intelligence

Role Description

At Booking.com, data drives our decisions. Technology is at our core and innovation is everywhere.

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, such as choosing and surfacing 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 such 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.
• Ensure implementation of reusable frameworks with clean and scalable code.
• Conduct data analysis with detailed metrics to evaluate model performance, label quality, and feature exploration.
• Work closely with machine learning engineers to ensure the model's latency and throughput meet product requirements and ensure deployment of your model to production.
• Collaborate with multidisciplinary teams, including product managers, data scientists, and analysts, to understand business requirements and translate them into machine learning solutions.

Role Qualifications and Requirements:

• Advanced knowledge and experience in Computer Vision and Natural Language Processing, including engineering aspects of developing ML and Generative AI 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 similar.
• Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience) involving 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 across multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, and 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, along with 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 rather than title, developing your team and motivating them to achieve their goals, providing timely feedback, and managing key team performance indicators.

Benefits & Perks - Global Impact, Personal Relevance:

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 as 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.

Pre-Employment Screening

If 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.