Machine Learning Engineer III

Expedia, Inc.; Madrid; Presencial; EUR 55.500 - 78.000; Jornada completa

Descripción de la vacante

Expedia, Inc. is seeking a Machine Learning Engineer III for their B2B Applied Machine Learning Team based in Madrid. In this role, you'll design and build scalable ML systems and data pipelines, optimizing resources for recommendations, rankings, and pricing. You’ll collaborate with scientists to enhance production workflows and bring innovative solutions across teams.

The position requires a degree in Computer Science and at least 3 years of ML engineering experience. The salary range is €55,500 to €78,000, with potential to reach €89,000 based on performance.

Formación

• 3+ years of experience in Software, Data, or ML engineering roles.
• Strong knowledge of ML algorithms and model architectures.
• Experience in building scalable and reliable ML systems.

Responsabilidades

• Design and implement scalable ML infrastructure.
• Build and maintain efficient data pipelines.
• Optimize compute resources for ML systems.
• Implement monitoring and logging systems.
• Collaborate with ML scientists to streamline workflows.
• Research and integrate new technologies.

Conocimientos

Python

Machine Learning frameworks (TensorFlow, PyTorch)

Problem-solving skills

Data processing

Cloud platforms (AWS, GCP)

Educación

Bachelor’s or Master’s degree in Computer Science or related field

Herramientas

Docker

Kubernetes

Spark

Kafka

CI/CD tools (GitHub Actions)

Descripción del empleo

We are looking for a Machine Learning Engineer III to join the Expedia Group B2B Applied Machine Learning Team. Your role will involve designing, building, and maintaining the infrastructure for deploying machine‑learning solutions, managing data pipelines, and optimizing compute resources for our ranking, recommendation, and pricing optimization systems.

In this role, you will:

• Design and implement scalable ML infrastructure for training, deployment, and serving in batch and real‑time environments.
• Build and maintain efficient data pipelines for large‑scale processing and feature engineering.
• Optimize compute resources and improve model serving performance across ML systems.
• Implement robust monitoring, logging, and alerting systems, contributing to ML Ops practices including CI/CD pipelines.
• Collaborate closely with ML scientists to streamline the model development‑to‑production workflow.
• Research and integrate new technologies, mentor junior engineers, and communicate technical solutions to diverse stakeholders.

Experience and qualifications:

• You hold a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
• You have 3+ years of experience in Software, Data, or ML engineering roles (preferred).
• You bring strong problem‑solving skills, proficiency in Python, and experience with ML frameworks such as TensorFlow or PyTorch.
• You understand ML algorithms, model architectures, and enjoy building scalable, reliable ML systems.
• You have exposure to cloud platforms (e.g., AWS, GCP), containerization (Docker, Kubernetes), and scalable data systems (e.g., Spark, Kafka).
• You are familiar with CI/CD tools (e.g., GitHub Actions), ML model serving technologies (e.g., MLflow), and collaborate well across teams.

The total cash range for this position in Madrid is €55,500.00 to €78,000.00. Employees in this role have the potential to increase their pay up to €89,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Welcome candidates who can demonstrate strong, language‑agnostic problem‑solving abilities and a passion for building robust ML systems, even if you do not fulfill every single requirement listed above. If you believe you can perform the job and are excited to grow with us, we’d love to hear from you.

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.