PhD Machine Learning Research Intern at Booking.com

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

26 Apr, 26

Salary

0.0

Posted On

26 Jan, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Natural Language Processing, Data-Centric AI, PyTorch, Python, NLP Libraries, Analytical Skills, Problem-Solving Skills, Written Communication, Verbal Communication, Independent Work, Research Skills

Industry

Software Development

Description

About Us: 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 encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world. About the team: The internship is open for PhD students in a machine learning related field like Planning with LLMs, Multilingual Training Adaptation, Recommender System and Ranking, Bidding, Synthetic Data Generation, Entity Representation Learning, Reinforcement learning and Classification. Applicants are asked to attach with their CV the email address of their supervisor or co-supervisor. This email will be used to ask for a recommendation letter at a later date. Please complete your application before March 31st, 2026. Participation in the internship program requires that you are located in Israel for the duration of the internship program (3 months) Role Description: As a Machine Learning Research intern at Booking.com in Tel-Aviv, 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. You will join us for a 3-month internship (preferred start date: May) focused on Data-Centric AI. In this project, you will tackle the "glass ceiling" of NLU performance: inherent ambiguity in annotation guidelines and label taxonomies. You will move beyond traditional noise reduction to investigate why human annotators disagree and how these disagreements corrupt "ground truth," directly influencing how we evaluate and improve state-of-the-art models. Key Job Responsibilities and Duties: Survey the Landscape: Conduct a comprehensive literature review to synthesize current approaches to data ambiguity, identifying the strengths and limitations of existing methods in handling label noise and taxonomy gaps. Innovate & Design: Devise novel techniques and metrics to detect, quantify, and resolve inherent ambiguities within NLP datasets and annotation guidelines. Experiment & Validate: Design and execute rigorous experiments to evaluate your proposed methods, measuring their impact on model reliability and ground truth accuracy. Publish Findings: Summarize your conclusions and contribute to writing a research paper with the aim of submitting to a top-tier NLP conference (e.g., ACL, EMNLP). Qualifications & Skills: Active PhD student in Computer Science, Computational Linguistics, Machine Learning, or related field. Proven experience with NLP projects involving tasks such as: Intent detection/recognition, Named Entity Recognition (NER), Sentiment analysis, or Entity extraction. Strong expertise in PyTorch and proficiency in Python and common NLP/ML libraries (huggingface, scikit-learn, pandas, numpy). Excellent analytical and problem-solving skills. Strong written and verbal communication abilities. Ability to work independently and drive research forward. 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.

Responsibilities

The intern will conduct a literature review on data ambiguity and develop novel techniques to address inherent ambiguities in NLP datasets. They will also design experiments to validate their methods and contribute to a research paper for submission to a top-tier NLP conference.