ML Scientist II — Scalable Recommender Systems

Expedia Group; Madrid; On-site; EUR 43,000 - 61,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision coverage

Paid time off

Employee Assistance Program

Wellness stipend

Travel reimbursement

Travel discounts

IATAN membership

Job summary

Expedia Group is seeking a Machine Learning Scientist II to build end-to-end ML solutions for personalized recommendations, learning to rank, and relevance optimization in Madrid. The role emphasizes scalable models, cross-functional collaboration, and a test-and-learn culture.

The candidate should have a PhD or Master’s in a relevant field, strong Python/PySpark skills, experience with ML libraries, and familiarity with Hadoop/Spark and AWS/GCP.

Qualifications

• PhD or Master’s in CS/ML/Math/Statistics or related field.
• 2 years of industry ML experience desirable but not required.
• Proficiency in Python with PySpark and ML libraries such as scikit-learn, TensorFlow, and Keras.
• Familiarity with Hadoop, Spark and cloud platforms (AWS, GCP).
• Strong understanding of ML algorithms and statistics.
• Excellent problem-solving and communication skills.

Responsibilities

• Develop ML models for recommendations & relevance at scale.
• Contribute to end-to-end ML solutions from data preprocessing to production deployment.
• Design and run A/B tests to improve algorithm performance.
• Stay current with ML techniques and contribute to team capabilities.
• Collaborate with cross-functional teams to translate business needs into technical solutions.
• Communicate methodologies and results clearly to technical and non-technical audiences and deploy models.

Skills

Problem-solving

Communication

Learning agility

Enthusiasm for ML

Education

PhD or Master's in CS/ML/Math/Statistics

Tools

Python

PySpark

scikit-learn

TensorFlow

Keras

Hadoop

Spark

AWS

GCP

Job description

Expedia Group is seeking a Machine Learning Scientist II to build end-to-end ML solutions for personalized recommendations, learning to rank, and relevance optimization in Madrid. The role emphasizes scalable models, cross-functional collaboration, and a test-and-learn culture.

The candidate should have a PhD or Master’s in a relevant field, strong Python/PySpark skills, experience with ML libraries, and familiarity with Hadoop/Spark and AWS/GCP.