Machine Learning Engineering Manager - Ranking and Recommendations Track

Booking Booking · Hospitality · Amsterdam, Netherlands · ML Engineering

Machine Learning Engineering Manager for the Ranking and Recommendations track at Booking.com. This role leads a team focused on foundational ML & Data layers for personalization systems, including search ranking and recommendations. Responsibilities include developing scalable ML infrastructure and pipelines, enabling ML scientists to productionize RecSys solutions, managing ML engineers and data engineers, and collaborating with stakeholders to translate business requirements into ML solutions. The role requires experience in leading ML engineering teams, deploying end-to-end ML models, and working with cloud frameworks and big data technologies.

What you'd actually do

  1. Lead and develop a high-performing team, fostering individual growth and collaboration.
  2. Manage and mentor ML engineers and Data engineers, ensuring their professional development and effectiveness.
  3. Develop scalable ML infrastructure and pipelines for efficient data processing and evaluations deployment.
  4. Evaluate architecture solutions based on cost, business needs, and emerging technologies.
  5. Collaborate closely with software engineers to ensure seamless deployment and model inference.

Skills

Required

  • Python
  • Java
  • Kafka
  • Hadoop
  • SQL
  • Spark
  • AWS sagemaker
  • TensorFlow
  • PyTorch
  • scikit-learn
  • Pyspark
  • Apache Flink
  • Snowflake
  • MySQL
  • Cassandra
  • DynamoDB
  • Recommender Systems
  • Deep Learning
  • Information Retrieval
  • Causal Inference
  • scaling ML models
  • end-to-end ML model deployment
  • cloud frameworks
  • big data processing frameworks
  • relational/NoSQL database systems
  • machine learning algorithms
  • statistical models
  • data structures
  • cross-functional collaboration
  • version control systems
  • English communication skills

Nice to have

  • leading an ML engineering team of a minimum of 4 people
  • MSc + 5 years of working experience
  • PhD + 3 years of working experience

What the JD emphasized

  • 3+ years leading an ML engineering team of a minimum of 4 people in a fast-paced production environment
  • Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.)
  • Strong knowledge in areas like e.g. Recommender Systems, Deep Learning, Information Retrieval, Causal Inference, scaling ML models, etc.
  • Experience designing and executing end-to-end solutions for deploying different ML models.

Other signals

  • personalize and optimize the customer experience
  • powering the ML for critical customer touch points like search results ranking and property/destination recommendations
  • lead the implementation of the tools for ML scientists to test and productionize advanced ML RecSys solutions
  • develop scalable ML infrastructure and pipelines
  • deploying different ML models
  • model inference