Machine Learning Engineer II

Private Label Solutions (PLS) is the B2B arm of Expedia Group. We bring Expedia Group's innovative technology and distribution solutions to partners across the world. These businesses include global financial institutions, corporate managed travel, offline travel agents, global travel suppliers (like major airlines) and many more …

We are looking for a Machine Learning Engineer II to join the Private Label Solutions (PLS) Machine Learning Engineering. You will join a team that builds and maintains the infrastructure for deploying ML solutions, managing data pipelines, and optimizing compute resources for our ranking problems, recommendation engines, and pricing optimization systems. Your work will contribute substantial value to our partners and EG by ensuring our ML models are efficiently deployed, scaled, and monitored in production environments.

This role offers a unique opportunity to work on diverse challenges and contribute to cutting-edge solutions that drive significant impact for the business. You will gain expertise in ML infrastructure, data engineering, cloud computing, and scalable system design while working closely with our ML scientists to bring their models to life in production.

This role requires an individual with a strong foundation in software engineering and machine learning infrastructure, who is passionate about building robust and scalable systems. You should be comfortable with ambiguity, enjoy tackling complex technical challenges, and have a keen interest in optimizing ML workflows.

We welcome candidates who are strong problem solvers and passionate about building ML systems. Even if you don’t meet every single requirement listed below. If you believe you can do the job and are excited to grow with us, we’d love to hear from you.

In this role, you will:

• Design and implement scalable infrastructure for deploying ML models in production.

• Build and maintain data pipelines for efficient processing and feature engineering.

• Optimize compute resources and enhance model serving performance.

• Set up monitoring and logging systems for deployed ML models.

• Collaborate with ML scientists to streamline development-to-production workflows.

• Improve CI/CD processes, contribute to A/B testing frameworks, and uphold ML engineering best practices.

Experience and qualifications:

• You hold a Bachelor’s or Master’s in Computer Science, Software Engineering, or a related field.

• You have 2+ years of experience in Software, Data, or ML engineering roles (preferred).

• You bring strong problem-solving skills, proficiency in Python, and familiarity with ML frameworks like TensorFlow or PyTorch.

• You have exposure to cloud platforms (e.g., AWS, GCP), containerization (Docker, Kubernetes), and scalable data systems (e.g., Spark, Kafka).

• You are experienced or interested in ML model serving technologies (e.g., MLflow, TensorFlow Serving) and CI/CD tools (e.g., GitHub Actions).

• You understand ML algorithms and collaborate effectively with cross-functional teams through strong communication skills.