machine learning engineer for travel LLMs

Booking.com develops travel-related chatbots, text generation and summarization applications, Q&A systems, free-text search, and travel-domain large language models with advanced agentic capabilities. Its solutions help redefine how travelers plan, book, and experience their journeys.

• Design, build, and maintain scalable infrastructure for training and fine-tuning large language models on Booking.com's extensive data;
• Optimize model serving and inference pipelines for latency, throughput, and cost efficiency at production scale;
• Develop and maintain ML pipelines for data processing, model training, evaluation, and deployment;
• Implement model optimization techniques such as quantization, distillation, pruning, and efficient attention mechanisms to meet production requirements;
• Build monitoring, alerting, and observability systems for deployed ML models, ensuring reliability and performance in production;
• Collaborate closely with ML scientists to translate research prototypes into production-grade systems;
• Contribute to reusable ML frameworks, tools, and libraries that accelerate the team's velocity;
• Ensure code quality, scalability, and maintainability through testing, code reviews, and documentation.

• Strong software engineering skills with deep experience building and deploying ML systems at scale;
• Hands-on experience with LLM training infrastructure, including distributed training, GPU clusters, PyTorch, DeepSpeed, FSDP, or Megatron-LM;
• Experience with model serving and optimization using vLLM, TensorRT, ONNX, Triton Inference Server, or similar tools;
• BSc with 4 years of work experience, or MSc with 3 years of work experience, in software engineering focused on machine learning systems;
• Bachelor's, Master's degree, or equivalent experience in Computer Science, Software Engineering, or a related quantitative field;
• Strong proficiency in Python;
• Experience with cloud infrastructure, Kubernetes, Docker, AWS/GCP, and distributed computing frameworks such as Spark or Ray;
• Familiarity with ML experiment tracking, CI/CD for ML, and data versioning tools;
• Experience with large-scale data processing pipelines using Kafka, Hadoop, Spark, Airflow, or similar tools;
• Understanding of NLP and LLM concepts;
• Ability to collaborate effectively with ML scientists and cross-functional teams;
• Excellent English communication skills, both written and verbal;
• Proven ability to work in a fast-paced, collaborative environment;
• Nice to have: experience with Java, C++, or CUDA.

• Annual paid time off and generous paid leave, including 22 weeks of paid parental leave, grandparent leave, bereavement leave, and care leave;
• Flexible working arrangements, work-from-home furniture, ergonomic support, and up to 20 days per year working from abroad in the home country;
• Sustainable HQ campus in Amsterdam with on-site meals, coffee, snacks, multi-faith rooms, and breastfeeding rooms;
• Commuting allowance and bike reimbursement scheme;
• Discounts and wallet credits for Booking.com products, Booking.com Genius Level 3 upgrade, and friends and family discount vouchers;
• Free access to online learning platforms, development and mentorship programs;
• Global Employee Assistance Program and free Headspace membership;
• Reasonable adjustments are available for individuals with disabilities during the interview process;
• Equal opportunity workplace and affirmative action employer;
• Pre-employment screening may be conducted by a third party if the application is successful.