Machine Learning Engineer - Trust & Safety

Join Booking.com as a Machine Learning Engineer in Trust & Safety

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: The Trust & Safety Machine Learning team is dedicated to safeguarding Booking.com's platform by building and deploying end-to-end Machine Learning solutions. We focus on developing robust models for detection, prevention, and proactive intervention against various trust and safety threats, leveraging data and advanced NLP techniques to create a secure environment for our users. Our work directly contributes to maintaining user trust and platform integrity.

Role Description: As a Machine Learning Engineer at Booking.com, you will play a key role in shaping how millions of travelers experience our products. You’ll work closely with ML scientists, software engineers, and product managers to turn business challenges into scalable, reliable ML solutions. Beyond delivery, you’ll also contribute to applied research and reusable frameworks, ensuring Booking.com remains at the forefront of AI innovation.

Key Job Responsibilities and Duties:

• Develop production-grade ML systems, from models to features and pipelines, accounting for reliability, scalability, real-time requirements, monitoring and retraining.
• Build readable and reusable code, applying code quality best practices and using standard libraries. Choose the right technology or coding methodology as well as refactor and simplify code when necessary.
• Take full ownership of your services end to end by actively monitoring the systems health, performance and business impact.
• Be responsible for business related data governance processes, the technical implementation and maintenance of data processing services and storage systems, and the implementation and maintenance of ML governance processes.
• Evaluate possible architecture solutions taking into account the business and technology requirements.
• Set the relevant service level objectives (SLOs) and act accordingly when they are not met.
• Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies and upskilling on these, as needed.
• Contribute to the internal ML/AI community by sharing your knowledge and participating in our internal ML programs.
• Coach others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
• Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of disciplines and related fields.
• Achieve mutually agreeable solutions by staying adaptable, communicating ideas in clear coherent language and practising active listening.

Required Qualifications and Skills:

• Bachelor’s or master’s degree in Computer Science, Engineering, Statistics, or a related field.
• Minimum of 4 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 as 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 (advantageous).
• Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib (advantageous).
• Experience with experimental design, A/B testing, and evaluation metrics for ML models (advantageous).
• Experience working on products that impact a large customer base (advantageous).
• Excellent communication in English; written and spoken.

Benefits & Perks - Global Impact, Personal Relevance:

• 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.
• Living and working in Amsterdam, one of the most cosmopolitan cities in Europe.
• 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.