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Booking.com

Machine Learning Engineer II - GenAI applications

Booking.com is hiring a Machine Learning Engineer II - GenAI applications in Tel Aviv, Israel. Level rates it ; you can apply on Booking.com.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting mentions PyTorch, TensorFlow and scikit-learn among its tools and skills.
  • Level classes it as a mid-level role.
  • Booking.com has 133 other open roles on Level.
  • Posted within the past two weeks.

AI in this role

pytorchtensorflowscikit-learnsagemaker
llm-integration

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.

 

Leadership/Team Quote:

This opening is for the GenAI Applications Team within the Data & AI Marketplace department.

The GenAI Applications team is responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and trip helpfulness. The team builds AI-driven applications and conversational agents, such as chatbots and intelligent assistants, that significantly enhance the end-to-end customer experience.

 

Role Description: 

In this role, you will design, build, and operate production-grade AI/machine learning applications for GenAI products. You will integrate foundation models with data, services, and tools; build agent workflows and own the systems end to end, including their reliability, observability, tracing, and quality. You will work closely with software engineers, ML scientists, and product teams to deliver scalable applications for travelers.

 

Key Job Responsibilities and Duties: 

  • Design, build, and productionize AI and agent-based systems by integrating LLMs with data, services, tools, and ML models. Develop the workflows needed to deliver complete product experiences, ensuring they are scalable, efficient, reliable, and accurate.

  • Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.

  • Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.

  • Build and maintain production-grade ML applications and tooling, including service and API integrations, testing, deployment, and CI/CD. Work with software engineers and DevOps to ensure reliable inference and maintainable operation in production.

  • Own ML applications and services end to end. Instrument them with metrics, logs, and traces; monitor application health, performance, reliability, and model output quality; and investigate issues and drive improvements when targets are not met.

  • Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.

  • Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. 

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 Engineer or a similar role, with a consistent record of successfully delivering ML solutions.

  • Strong programming skills in Python and experience building tested, maintainable production services or applications; experience with Java is also an advantage.

  • Experience deploying and operating ML models and applications in cloud environments, including model serving, monitoring, and CI/CD.

  • Evaluating model and application quality, monitoring quality in production, and using traces and metrics to diagnose failures and guide improvements.

  • Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.

  • Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

  • Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks.

  • Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

  • Deep understanding of machine learning algorithms, statistical models, and data structures.

  • Experience in deploying large-scale language models like GPT, BERT, or similar architectures - an advantage.

  • Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.

  • Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.

  • Experience of working on products that impact a large customer base - an advantage.

  • Excellent communication in English; written and spoken.

 

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: 

This section should provide: 

  • 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 Engineer II - GenAI applications at Booking.com rates 95 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

LLM IntegrationPyTorchTensorFlowscikit-learnSageMaker

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$200k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How have you integrated a large language model into a production application?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. What's a project where you used scikit-learn hands-on?
  5. Walk me through how you've used SageMaker in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: LLM Integration, PyTorch, TensorFlow, scikit-learn, and SageMaker. 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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