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Booking.com

Machine Learning Scientist II - Content Intelligence

Booking.com is hiring a Machine Learning Scientist II - Content Intelligence in Tel Aviv, Israel. Level rates it ; you can apply on Booking.com.

Level's read on this job

  • Level rates this role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include LangChain, Python and LLMs.
  • Level classifies it as a mid-level role.
  • Level lists 127 other open roles at Booking.com.
  • The role was posted in the last few days.

AI in this role

Design, train, evaluate, and deploy scalable GenAI solutions, LLMs, and agentic workflows for core platform features.

langchainpythonllms
ai-agentsfine-tuningcomputer-visionnlpmachine-learninggenai

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:

This opening is for the Supply Intelligence team within the Data & AI Marketplace department.

The Supply Intelligence team builds the core AI intelligence layer powering the platform by transforming complex, multimodal booking data, including millions of customer reviews and property, attractions, city images into high-impact applications. You will be actively developing ML solutions and implementing reusable ML frameworks/GenAI pipelines end-to-end. Your work will directly power core features such as automated review summarization, AI-generated property descriptions, property embeddings, and intelligent photo gallery selection and optimization, image captioning, text sentiment, driving real-world business value through fast, incremental builds from MVP to production.

Role Description:

As a Machine Learning Scientist II, you will collaborate with cross-functional engineering and product teams to design, train, evaluate, and deploy scalable GenAI solutions for customer-facing products. In this role, you will build advanced NLP, computer vision, and LLM-driven agentic architectures, establish robust evaluation frameworks, and drive measurable business outcomes through data driven experimentation.

Key Job Responsibilities and Duties:

  • Hands-On Execution & Fine-Tuning: Directly write code to build, fine-tune, and optimize state-of-the-art LLMs and agentic workflows.

  • Requirements to Incremental Builds: Translate product requirements into technical specifications and build solutions incrementally, starting with fast, functional MVPs and systematically evolving them into complex, scalable systems.

  • Pragmatic, Applied Research: Lead lean, highly targeted research sprints to rapidly extract actionable insights and translate them directly into production code, balancing innovation with speed to production delivery.

  • Problem-Solver Mindset: Take end-to-end ownership of technical challenges, using strong analytical debugging to overcome algorithmic, mathematical, and implementation bottlenecks.

  • Production Evaluation: Set up rigorous evaluation pipelines, define concrete metrics including judge LLMS, and continuously benchmark models on real-world customer data to iteratively improve product performance.

  • End-to-End Production & Engineering Collaboration: Work side-by-side with Machine Learning Engineers to optimize model latency and throughput, ensuring smooth deployment and high performance in live environments.

  • Production-Grade Clean Code: Write modular, clean, and scalable code to build reusable ML frameworks, ensuring long-term maintainability and software engineering rigor.

Qualifications & Skills:

  • Bachelor’s or master’s degree in Computer Science, Engineering, Statistics, or a related field.

  • Minimum of 3 years of experience as a Machine Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions to production.

  • Strong understanding and practical experience with Generative AI models, Natural Language Processing and engineering aspects of developing ML.

  • Experience executing research and development plans and contributing to large-scale ML applications.

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

  • Experience collaborating cross-functionally in the development of ML products (e.g. Developers, Product Managers, UX specialists, etc.).

  • Strong working knowledge of Python, LangChain, SQL, and Spark or similar technologies.

  • Strong coding practices, including writing and reviewing production-quality, maintainable, and well-tested code, with the ability to effectively leverage modern AI coding assistants while maintaining high standards for correctness, readability, and system design.

  • Excellent English communication and presentation skills, both written and verbal.

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:

  • 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

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

  • 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 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.

How we rate this

Machine Learning Scientist II - Content Intelligence at Booking.com rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsFine-tuningComputer visionNLPMachine learningGenAILangChainPython

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  4. What NLP problem have you worked on, and how did you measure whether it actually worked?
  5. Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, Fine-tuning, Computer vision, NLP, and Machine learning. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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