As a Machine Learning Engineering Manager, you will lead a team focused on the foundational ML & Data layers to power the ranking & recommendation systems in scope. You will drive the development of robust data & ML pipelines at scale, lead the implementation of the tools for ML scientists to test and productionize advanced ML RecSys solutions.
Key Job Responsibilities and Duties:
Lead and develop a high-performing team, fostering individual growth and collaboration.
Manage and mentor ML engineers and Data engineers, ensuring their professional development and effectiveness.
Develop scalable ML infrastructure and pipelines for efficient data processing and evaluations deployment.
Evaluate architecture solutions based on cost, business needs, and emerging technologies.
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 team.
Qualifications & Skills:
3+ years leading an ML engineering 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.).
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.
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. We offer a competitive , as well unique-to-Booking.com benefits which include:
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 29 days per year working from abroad (home country)
Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit
Application Process:
Let’s go places together: 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.
