gistfile1.txt

Machine Learning Scientist II - Content Intelligence

About the job
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 make. The journeys you take. The sights you see. And the food you sample. Through our products, partners and people, we can empower everyone to experience the world.

The Content Intelligence team builds the Content Intelligence Platform by consuming millions of images and textual inputs every day, and then enriching it with ML capabilities. Eventually, these will serve downstream applications and personalize our customers' experience (think of a way to choose and surface the right images and reviews when customers book their next vacation).

Moreover the team is taking a key role in building in-house LLMs for different needs as: moderation, translation, AI trip planner chatbot, content generation and other GenAI applications.

About the role:

As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.

You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.

Key Job Responsibilities and Duties:

Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning…), build algorithms, and engineering approaches to drive business impact.. 
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate model’s performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
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: 

Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and GenerativeAI models at scale.
Experience designing and executing end-to-end research and development plans and generating impact through large-scale machine learning model development. Preferably evidenced by peer-reviewed publication, patents, open sourced code or the like.
Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience), involved in the application of Machine Learning to business problems.
Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
Excellent English communication skills, both written and verbal.
Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators

gistfile2.txt

Senior AI Backend Software Engineer I - AI Application Platform

Role Description

Our mission at Booking.com is to create visionary, innovative, and personalised travel experiences for millions of customers worldwide. Across our offices worldwide, we continue to innovate by solving some of the most complex challenges in travel and technology and plan for the exciting developments that lie ahead through strategic long-term investments in what we believe the future of travel can be.

As a Software Engineer working on the AI Application Platform, you will work at the intersection of scalable backend systems and cutting-edge AI. You will have the opportunity to design and build the core platform that enables product teams to rapidly develop and deploy AI-powered experiences for millions of people. You will tackle complex performance and scaling challenges, shape the foundation of our AI infrastructure, and collaborate closely with ML engineers, data engineers, and data scientists to bring intelligent systems into production at scale.

For more insights about the different business units and the scope of their projects and goals, please visit this page.

Key Responsibilities & Duties

Important aspects of the job can include:

Design and evaluate architecture solutions for AI infrastructure, rapidly prototyping to validate key assumptions and guide decision-making.
Explore, benchmark, and integrate new AI/ML tools and technologies to drive innovative engineering solutions that meet evolving business needs.
Build and maintain scalable, reusable backend services that support real-time AI/ML inference, model deployment, and data pipelines.
Collaborate closely with ML engineers, data engineers, and data scientists to bring AI/ML models into production and optimize system performance.
Take end-to-end ownership of system reliability and operational excellence, including performance tuning, observability and incident management.
Continuously grow technical and interpersonal skills through hands-on experience, knowledge sharing sessions, and industry events.


Role Qualifications & Requirements

We are looking for driven Software Engineers who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right approach and tools.

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

Experience in feature engineering, integrating AI/ML models into production systems, and understanding model behavior, performance and constraints.
Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration.
Experience working in cross-functional teams alongside ML engineers, data scientists, and product stakeholders to bring AI/ML products to production. 
7+ years of professional experience in software engineering, with a focus on backend or platform development.
Experience building distributed systems at scale, with a focus on performance tuning, observability, and reliability best practices.
Experience with scalable data storage systems (e.g. MySQL, Redis) and optimizing data access and caching for high-throughput applications.
Proficiency in one or more server-side programming languages such as Java, Scala, or Python.
Experience with containerization tools like Docker and Kubernetes, and deploying applications in cloud environments such as AWS or GCP.
Ability to navigate ambiguity, take ownership of complex problems, and drive them to resolution.
Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent industry experience.

gistfile3.txt

AI Backend Software Engineer II - AI Application Platform

Role Description

Our mission at Booking.com is to create visionary, innovative, and personalised travel experiences for millions of customers worldwide. Across our offices worldwide, we continue to innovate by solving some of the most complex challenges in travel and technology and plan for the exciting developments that lie ahead through strategic long-term investments in what we believe the future of travel can be.

As a Software Engineer working on the AI Application Platform, you will work at the intersection of scalable backend systems and cutting-edge AI. You will have the opportunity to design and build the core platform that enables product teams to rapidly develop and deploy AI-powered experiences for millions of people. You will tackle complex performance and scaling challenges, shape the foundation of our AI infrastructure, and collaborate closely with ML engineers, data engineers, and data scientists to bring intelligent systems into production at scale.

For more insights about the different business units and the scope of their projects and goals, please visit this page.

Key Responsibilities & Duties

Important aspects of the job can include:

Design and evaluate architecture solutions for AI infrastructure, rapidly prototyping to validate key assumptions and guide decision-making.
Explore, benchmark, and integrate new AI/ML tools and technologies to drive innovative engineering solutions that meet evolving business needs.
Build and maintain scalable, reusable backend services that support real-time AI/ML inference, model deployment, and data pipelines.
Collaborate closely with ML engineers, data engineers, and data scientists to bring AI/ML models into production and optimize system performance.
Take end-to-end ownership of system reliability and operational excellence, including performance tuning, observability and incident management.
Continuously grow technical and interpersonal skills through hands-on experience, knowledge sharing sessions, and industry events.


Role Qualifications & Requirements

We are looking for driven Software Engineers who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right approach and tools.

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

3+ years of professional experience in software engineering, with a focus on backend or platform development.
Experience building distributed systems at scale, with a focus on performance tuning, observability, and reliability best practices.
Experience with scalable data storage systems (e.g. MySQL, Redis) and optimizing data access and caching for high-throughput applications.
Proficiency in one or more server-side programming languages such as Java, Scala, or Python.
Experience in feature engineering, integrating AI/ML models into production systems, and understanding model behavior, performance and constraints.
Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration.
Experience working in cross-functional teams alongside ML engineers, data scientists, and product stakeholders to bring AI/ML products to production. 
Experience with containerization tools like Docker and Kubernetes, and deploying applications in cloud environments such as AWS or GCP.
Ability to navigate ambiguity, take ownership of complex problems, and drive them to resolution.
Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent industry experience.