Machine Learning Engineer, Booking.com
Travel LLMs Modeling
Leading travel accommodation and experiences marketplace
Job no longer available
Leading travel accommodation and experiences marketplace
1001+ employees
Job no longer available
1001+ employees
Company mission
To shape the future of travel through cutting edge technology, to make it easier for everyone to enjoy amazing experiences wherever they go.
Role
Who you are
- Strong software engineering skills with deep experience in building and deploying ML systems at scale
- Hands-on experience with LLM training infrastructure (distributed training, GPU clusters, frameworks like PyTorch, DeepSpeed, FSDP, or Megatron-LM)
- Experience with model serving and optimization (e.g., vLLM, TensorRT, ONNX, triton inference server, or similar)
- Relevant work or academic experience (BSc + 4 years of working experience, or MSc + 3 years of working experience) in software engineering with a focus 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 Java, C++, or CUDA is a plus
- Experience with cloud infrastructure and orchestration (Kubernetes, Docker, AWS/GCP) and distributed computing frameworks (Spark, Ray, or similar)
- Familiarity with ML experiment tracking, CI/CD for ML, and data versioning tools
- Experience with large-scale data processing pipelines (Kafka, Hadoop, Spark, Airflow, or similar)
- Understanding of NLP/LLM concepts and the ability to collaborate effectively with ML scientists on model development
- Excellent English communication skills, both written and verbal
- Proven ability to work in a fast-paced, collaborative environment with cross-functional teams (ML scientists, product managers, developers)
What the job involves
- The team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search
- The team you are applying to is spearheading a research effort to develop leading LLMs, specifically designed for the travel domain and advanced agentic capabilities
- This pioneering initiative combines cutting-edge AI research with practical applications, focusing on creating tailored solutions that redefine how travelers plan, book, and experience their journeys
- As a Machine Learning Engineer, you will be responsible for building and maintaining the infrastructure, systems, and pipelines that enable the training, optimization, and deployment of cutting-edge Generative AI models at scale
- This includes developing robust training pipelines for foundation models, optimizing model serving for low-latency inference, and ensuring production reliability for systems that serve millions of travelers daily
- Your engineering expertise will be critical in bridging the gap between research breakthroughs and production-ready AI systems
- 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 the development of reusable ML frameworks, tools, and libraries that accelerate the team's velocity
- Ensure code quality, scalability, and maintainability through best engineering practices including testing, code reviews, and documentation
Our take
Booking.com has established itself as a leading digital travel company. The company reaps the benefits of its status in the market and is currently in a stronger position than its up-and-coming competitors such as Expedia, Trivago and Trip.com. Airbnb represents the sharing economy and acts as a disruptive force in this market but still has ways to go to compete with Booking.com.
In recent years, there has been considerable growth in the number of travellers wishing to travel more sustainably. And Booking.com is well positioned to attract these consumers, having introduced a Travel Sustainable badge on their platform which over 100,000 properties have achieved for their sustainability efforts.
The company was originally founded with a core focus on hotels, and the platform now offers more than 31M accommodation listings. It has also expanded into different services, including flights, car rentals, and attractions.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Company benefits
- Health insurance
- Free access to Headspace for you and your loved ones
- Global Employee Assistance Program
- Meditation and Breastfeeding rooms at the office
- Booking Cares - 2 days per year to volunteer and learn
- Life insurance
- Disability insurance
- Pension plan
- Annual paid time off
- Parental leave - 22 weeks
- Grandparent leave - 10 days
- Care leave - 10 days
- Bereavement leave - up to 4 weeks
- Anniversary leave
- Working from Home Furniture and Ergonomic Support
- Working from Abroad - up to 20 days per year
- Discounts & Wallet credits to spend on our products
- Upgrade to Booking.com Genius Level 3
- Friends & Family Booking.com discount vouchers
- Free access to online learning platforms
- Development and mentorship programs to support career growth
- Access to trainings and workshops
- Team development opportunities
- Local discount programs
- Game rooms in offices
- On-site meals, coffee and snacks including vegan options
Company HQ
Nieuwmarkt en Lastage, Amsterdam, Netherlands
Leadership
Glenn Fogel
(CEO)Previously Vice President at Morgan Stanley. They joined Booking Holdings in 2000 and have held several high profile and executive positions since. They are currently the President and CEO
Salary benchmarks
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