Senior Machine Learning Engineer I - GenAI Applications
Job Description
About Us: 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 encounter
The journeys you take
The sights you see
And the memories you make
Through our products, partners and people, we make it easier for everyone to experience the world.
Leadership/Team Quote:
This opening is for the GenAI Infra team in the Marketplace AI department.
The GenAI Infra team builds the Agents platform at Booking.com which is used for all agnetic and non-agentic flows at Booking
This team is responsible for both the GenAI agents and the orchestration around them, helping support applications such as the AI Trip Planner, Free text search, etc.
Role Description:
As Senior Machine Learning Engineer, you’ll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience
The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.
Key Job
and Duties:
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
, emerging technologies, and technology
, 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
and translate them into machine learning solutions.
Qualifications & Skills:
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 LLMs, Agents and MCP in production environments.
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
but also about
We offer a competitive compensation and
package, as well unique-to-Booking.com
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
Diversity, Equity and Inclusion (DEI) at Booking.com:
Diversity, Equity & Inclusion have been a core part of our company culture since day one
This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations.
Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and more inclusive travel experience for everyone
Inclusion is at the heart of everything we do
It’s a place where you can make your mark and have a real impact in travel and tech.”
We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other
and privileges of employment.
Application Process:
Let’s go places together: How we Hire
This role does not come with relocation assistance.
Booking.com is proud to be an
workplace and is an affirmative action employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status
We strive to move well beyond traditional
and work to create an environment that allows everyone to thrive.
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
and suitability for the position.