Senior Machine Learning Engineer I

Role Description

About us:

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. Through our products, partners and people, we make it easier for everyone to experience the world.

About the team:

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.

As a Senior ML Engineer I in the Booking Ads ML team, you will design, build, and deploy scalable machine learning solutions for GenAI applications, focusing on LLMs and agent-based architectures using state-of-the-art techniques. You will be working closely with top-tier engineers and ML scientists to shape the future of intelligent travel products.

Key Responsibilities

• Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
• 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.
• Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
• Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
• 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.

Role Qualifications and Requirements:

We are looking for driven MLE’s who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right mindset and tools.

We have found that people who match the following requirements are the ones who fit us best:

• Bachelor’s or master’s degree in computer science, Engineering, Statistics, or a related field.
• Minimum of 6 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 languages such as Python and Java.
• 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
• 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
• Opportunity to utilize technical expertise, leadership capabilities and entrepreneurial spirit
• Promote and drive impactful and innovative engineering solutions
• 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

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.