Machine Learning Scientist II - Recommendation Platform

We are looking for driven MLSs who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right mindset and tools.
Key Job Responsibilities and Duties:
Data pre-processing and analysis: Collaborate with data engineers and machine learning engineers to collect, clean, pre-process, and transform large and wide datasets for model features and data monitoring. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.
Model Building: Utilize the data to design, train and build advanced recommendation models for different disciplines in Booking combining neural networks, LLMs and other SOTA technologies.
Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts from other teams to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.