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Booking Machine Learning Engineering Manager 
Israel, Center District, Nes Ziona 
901645854

02.08.2024

About the role:

In this position, you will be responsible for the development of horizontal platform capabilities and standardize Content Intelligence (CI) infrastructure and tools to ensure high quality and efficiency across CI products. You will lead our Content Intelligence Platform and GenAI engineering aspects, including data management, monitoring, modernization, and horizontal ML engineering initiatives such as model retraining pipelines and evaluation pipelines.

Key Job Responsibilities and Duties:

  • Lead and develop a high-performing team, fostering individual growth and collaboration.
  • Manage and mentor ML engineers, ensuring their professional development and effectiveness.
  • Develop scalable ML infrastructure and pipelines for efficient data processing and model deployment.
  • Evaluate architecture solutions based on cost, business needs, and emerging technologies.
  • Contribute to generative AI development, including novel applications like GPT variants.
  • Collaborate closely with software engineers to ensure seamless deployment and model inference.
  • Monitor application health, set and track relevant metrics, and implement effective maintenance strategies.
  • Collaborate with stakeholders to translate business requirements into viable ML solutions.
  • Evaluate and integrate new ML technologies to enhance productivity and performance.
  • Drive continuous improvement through model retraining, performance monitoring, and optimization.
  • Develop robust ML and AI solutions that meet business objectives while considering production constraints.
  • Stay abreast of industry methodologies, explore new technologies, and champion their adoption within the team.
  • Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, and mentoring colleagues.
  • Advocate for improvements, scaling, and extension of ML tooling and infrastructure.
  • Foster a culture of innovation, collaboration, and excellence within the ML engineering team.


Role Qualifications and Requirements:

  • 3+ years leading an ML team of a minimum of 4 people in a fast-paced production environment.
  • 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.
  • Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
  • Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and GenerativeAI models at scale.
  • Experience designing and executing end-to-end solutions for deploying different ML models.
  • Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.
  • Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or 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 collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
  • Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
  • Excellent English communication skills, both written and verbal.
  • Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
  • Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators

Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. Our Total Rewards strive to make it easier for you to experience all that life has to offer on your terms so that you can focus on what really matters. We offer competitive compensation as well as thoughtful, valuable, and even fun benefits which include:

  • Headquarters located in one of the most dynamic and cosmopolitan cities in Europe: Amsterdam.
  • Contribute to a high scale, sophisticated, world-class product and see the real time impact of your work on millions of travelers worldwide.
  • Be part of a truly international fast paced environment and performance driven culture.
  • Performance-based company that offers career advancement, and lucrative compensation, including bonuses and stock potential.
  • Discount on Booking.com accommodations with the “Booking Deal” including other perks and benefits.
  • Company-sponsored family and social activities to help our employees become integrated with each other and the company's culture.
  • Diverse and creative colleagues from every corner of the world.
  • Health, life, and disability insurance*
  • 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 for yourself, friends, and family, including automatic Genius Level 3 status and quarterly Booking.com wallet credit.
  • Free access to online learning platforms, development and mentorship programs, and a complimentary Headspace membership
  • On-site meals, coffee, and snacks, including healthy and vegan options, daily*

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.