Machine Learning Manager - Recommendations & Smart Positioning

Booking Booking · Hospitality · Amsterdam, Netherlands · ML Science

Machine Learning Manager for Recommendations & Smart Positioning team at Booking.com. The role involves leading a team of ML scientists to develop and deploy ML solutions for product ordering, recommendations, search optimization, and filters across the platform, managing billions of requests daily. Responsibilities include team building, roadmap definition, technical decision-making, and ensuring the delivery of innovative ML models and AI solutions within production constraints, impacting a large customer base.

What you'd actually do

  1. Build a strong team within their area, by coaching and developing individual contributors
  2. Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
  3. Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
  4. Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business. Design and execute applied research plans to understand, apply, test, evolve, and generalise these technologies into reusable frameworks.
  5. Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.

Skills

Required

  • Strong programming skills in languages such as Python and Java.
  • Experience with cloud frameworks like AWS sagemaker and training models using TensorFlow or PyTorch
  • Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks.
  • Deep understanding of machine learning algorithms, statistical models, and data structures.
  • Experience with experimental design, A/B testing, and evaluation metrics for ML models.
  • 3+ years leading an ML team of a minimum of 4 people in a fast-paced pro

Nice to have

  • Experience of working on products that impact a large customer base is an advantage
  • Advanced knowledge and experience in Recommendation systems, including engineering aspects of developing ML models at scale is an advantage.
  • 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.
  • 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.).
  • Excellent English communication skills, both written and verbal.

What the JD emphasized

  • managing a team of ML scientists
  • recommendation systems
  • large scale machine learning model development
  • production environment

Other signals

  • managing a team of ML scientists
  • recommendation systems
  • large scale ML model development
  • production environment constraints
  • customer funnel