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Booking Machine Learning Engineer II - Marketplace 
Netherlands, North Holland, Amsterdam 
967523253

Yesterday

Role Description

As a Machine Learning Engineer, your responsibility is to operationalise cutting-edge Machine Learning models that need to run in real-time, ensuring low-latency performance to deliver an exceptional user experience for our travelers, requiring the training of large-scale models and developing scalable feature engineering solutions using modern data and Machine Learning tooling and optimization techniques. You will work closely together with the other Machine Learning Engineers and Machine Learnings Scientists in the User Intent Modelling team as well as with Data Engineers, Software Engineers and Product Managers.

Key Job Responsibilities and Duties
  • Execute applied research plans for machine intelligence on a specific product by designing innovative ML/AI models, algorithms, and approaches that deliver both short-term commercial impact and longer-term differentiated business value and customer experiences. Document and share the findings.

  • Translate specific business problems into ML/AI challenges and identify the best approach within the constraints of the production environment. Build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders.

  • Develop production-grade machine learning code, from models to features and pipelines, allowing for scalability, realtime, monitoring and retraining. Monitor product health, performance and business impact and act accordingly when not met.

  • Build readable and reusable code, choosing the right technologies, coding methodologies, and approach from carefully designed rapid prototyping to software deployment at scale. Identify opportunities for platform-based development and reuse by abstracting business problems to generalized ML/AI solutions.

  • Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI disciplines and related fields. Coach others through evidence and clear communication, explaining advanced technical concepts.

  • Identify underlying issues and opportunities across domains and situations through application of structured thinking and logic, and formulate possible improvements.

  • Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies, introducing them to the machine learning community and promoting their application in areas where they can generate impact.

  • Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues.

  • Push for improvements, scaling and extending machine learning tooling and infrastructure, collaborating with central teams.

Role Qualifications and Requirements
  • We prefer candidates with Deep Learning experience, especially when applied to large-scale datasets.

  • 2 years of relevant work experience (or equivalent), involved with the application of Machine Learning to business problems in a commercial environment.

  • Demonstrable experience of multiple machine learning facets, such as working with large data sets, experimentation, scalability and optimization.

  • Experience with data-driven product development: analytics, A/B testing, etc.

  • Strong working experience in one or more general purpose programming languages, including but not limited to: Java, Python or Perl.

  • Strong working knowledge of Spark and SQL.

  • Bsc or higher in Computer Science, Artificial Intelligence, Software Engineering, or related fields.

  • Excellent English communication skills, both written and verbal.

  • Experience in Kubernetes and Docker.

: Global Impact, Personal Relevance
  • 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


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.