Role Description:
We are looking for a versatile ML expert, capable of handling all aspects from system architecture to coding, encompassing ML engineering, model design, and training. You will own the design and delivery of ML systems, from initial idea generation and collecting business requirements from product stakeholders to implementation. You will work closely together with the other Machine Learning Scientists and Machine Learning Engineers as well as with Data Engineers, Software Engineers and Product Managers.
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 and refactor and simplify code when necessary.
Take full ownership of services end-to-end by actively monitoring system health, performance, and business impact. Set relevant service level objectives (SLOs) and act accordingly when they are not met.
Combine innovation with reuse by abstracting ML/AI concepts from one application to a generalized framework, including leveraging published research, open-source technologies, and previously-developed products at Booking.
Be responsible for business-related data governance processes, technical implementation, and maintenance of data processing services and storage systems, as well as ML governance processes.
Evaluate possible architecture solutions considering business and technology requirements.
Contribute to the internal ML/AI community by sharing knowledge and participating in internal ML programs.
Coach others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
Achieve mutually agreeable solutions by staying adaptable, communicating ideas in clear coherent language, and practicing active listening.
Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies and upskilling as needed.
Qualifications & Skills:
- Masters, PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.).
- Minimum of 6 years of experience as a Machine Learning Engineer or a similar role, preferably with products that impact ideally millions of customers every day
- Be a versatile ML expert, capable of handling all aspects from system architecture to coding, encompassing ML engineering, model design, and training.
- Strong working experience in one or more general purpose programming languages, including but not limited to: Java or Python.
- Experience with big data processing frameworks such as Pyspark, Apache Flink, Snowflake or similar frameworks.
- Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.
- Deep understanding of machine learning algorithms, statistical models, and data structures.
- Demonstrated experience in technical leadership, including leading cross-functional teams, and driving technical initiatives to successful outcomes.
- Excellent communication and collaboration skills to work effectively with diverse crafts such as engineering, UX, and product management.
- (Strong plus) Experience in developing large-scale customer-facing search and recommendation systems in an e-commerce environment, including building and maintaining complex multi-stage recommender architecture in high-throughput and low-latency environments.
- (Nice to have) Experience with experimental design, A/B testing, and evaluation metrics for ML models.
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive , as well unique-to-Booking.com benefits which include:
Annual paid time off and generous paid leave scheme including: parental (22-weeks paid leave), grandparent, bereavement, and care leave
Hybrid working including flexible working arrangements, working from home furniture and ergonomic support, and up to 20 days per year working from abroad (home country)
A beautiful sustainable , that offers on-site meals, coffee, and snacks, multi-faith and breastfeeding rooms at the office*
Commuting allowance and bike reimbursement scheme
Discounts & Wallet credits to spend on our products, upgrade to Booking.com Genius Level 3, and friends & family Booking.com discount vouchers
Free access to online learning platforms, development and mentorship programs
Global Employee Assistance Program, free Headspace membership
Application Process:
- Let’s go places together:
- The interview process entails: an online coding challenge, a coding interview, a system design interview, and a final behavioral interview
- This role does not come with relocation assistance
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.
