PhD Machine Learning Research Intern

ask for a recommendation letter at a later date.

Please complete your application before March 1st, 2026. Participation in the internship program requires that you are located in The Netherlands for the duration of the internship program (3 months)

Role Description: As a Machine Learning Research intern at the headquarters of Booking.com in Amsterdam, you will have the opportunity to tackle real world problems by pushing the boundaries of the state-of-the-art, with the goal of publishing your work

Key Job Responsibilities and Duties:

• Work together with your project mentor and the team on an exciting project

• Be able to understand and extend the state of the art techniques to solve the project at hand

• Be able to publish your work in top conferences and journals

• Actively contribute to taking data science at Booking.com to the next level

Qualifications & Skills:

• Pursue your PhD degree in a quantitative field (e.g. Computer Science, Mathematics, Artificial Intelligence, Physics, etc).

• Ability to conduct research independently as evidenced by peer-review publication or similar track record.

• Excellent English communication skills, both written and verbal.

• Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.

• Strong working knowledge of Python; Hadoop, SQL, Spark or similar big data technologies.

Projects:

1. Regularized Target Encoding for large real-world datasets - the relevant skills are: deep learning applied to tabular data, experience with tensorflow (preferrably) or another python deep learning framework, (ideally) knowledge of Bayesian inference, familiarity with Variational Inference or other posterior approximation methods is a plus.

2. Multi-Agent Collaboration - the relevant skills are: experience with LLM-based agents; familiarity with multi-agent collaboration techniques

3. Aligning LLMs with user feedback via reinforcement learning - experience with RL methods applied to LLMs (GRPO, PPO, etc.); experience with RL frameworks like TRL or verl.

4. Multi-level treatments - knowledge of causal inference and counterfactual learning with continuous actions, or experience with statistics oriented operations research.

5. Interpretable Foundations: Explainability Methods for Transformer Models on Sequential Event Data - experience with (preferred published work on) designing neural networks, specifically transformer architectures; experience with (preferred published work on) explainability/interpretability measurement techniques for machine learning; experience working with tools such as sagemaker training, git and spark (not all necessary)

6. Scalable and generalisable ID embedding learning - the relevant skills are (in order of importance): experience with semantic ID; experience with deep learning models at scale; experience with Tensorflow and AWS

7. Improving property embeddings with better handling of rich and long-context data - the relevant skills are: experience with fine-tuning Large Language Models (LLMs) or Vision Large Language Models (vLLMs); experience with Python and (preferrably): PyTorch and Huggingface; experience with (applied) research projects in one of these fields: Information Retrieval; Ranking and Recommendation Systems; Semantic Search; Question Answering; Representation/Contrastive Learning

8. Utility-aware retrieval for context engineering in travel planning - the relevant skills are: knowledge of context engineering; experience using user feedback to optimize AI agents; dense retrieval architectures that optimize for objectives other than semantic similarity

9. Synthetic Data Generation in Images - the relevant skills are: Experience with LLM fine tuning (must have); Experience with developing LoRAs for Diffusion models (SDXL, Qwen-image, ....), experience with image to image workflows, experience with prompting diffusion models (SDXL, Flux, Qwen-image, ...); Experience using ComfyUI (nice to have)

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 unique-to-Booking.com benefits which include:

• Contributing to a high scale, complex, world renowned product and seeing real-time impact of your work on millions of travelers worldwide

• Working in a fast-paced and performance driven culture

• Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences and active community participation

• Competitive compensation and benefits package and some great added perks of working in the home city of Booking.com

• Vast amounts of data to validate your ideas and the opportunity to experiment with real users.

• 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

Diversity, Equity and Inclusion (DEI) at Booking.com:

Diversity, Equity & Inclusion have 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 more 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

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 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.