Machine Learning Engineer II

2 weeks ago


London, Greater London, United Kingdom Expedia Group Full time

About the Role

We're seeking a talented Machine Learning Engineer II to join our team at Expedia Group. As a key member of our cross-functional team, you'll be responsible for operationalizing machine learning models in production, building scalable systems for model development, data ingestion, feature engineering, inference, and monitoring/evaluation.

Key Responsibilities

  • Collaborate with ML Engineers and Scientists to develop and deploy machine learning models in production environments.
  • Design and implement scalable, high-performance systems for data processing, feature engineering, and model inference.
  • Provide accurate time estimates for projects, turn them into code, and deliver on schedule.
  • Advocate for quality coding practices, ensuring secure, stable, testable, and maintainable code with minimal defects.

Requirements

  • 2+ years of experience in machine learning and software engineering (Bachelor's) or 1+ years (Master's).
  • Experience working in a team environment with agile methodologies, version control, and coding proficiency in modern programming languages (Java, Scala, Python, etc.).
  • Strong background in data structures and algorithms, with experience working with machine learning frameworks (TensorFlow, PyTorch, XGBoost, etc.) and big data technologies (Spark, Kafka, Hive, Databricks, feature stores, etc.).
  • Experience with containerization, deployment, and orchestration technologies (Docker, Kubernetes, Airflow, CI/CD pipelines, etc.) and automated testing (unit, functional, and integration testing).
  • Excellent organizational and communication skills, with a Bachelor's or Master's degree in Computer Science or a related field.

What We Offer

At Expedia Group, we're committed to creating a workplace that's inclusive, diverse, and rewarding. As a Machine Learning Engineer II, you'll have the opportunity to work with a talented team, develop your skills, and contribute to the success of our company.



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