Machine Learning Engineer III

Introduction to the Team

We create and deliver an aligned, dedicated marketing strategy to fuel each Expedia Group brand's success. Since our travelers interact with us through our brands, we maintain a brand-focused approach in our marketing while leveraging the scale and efficiency we’ve built through functional expertise.

The Meta/SEM Bidding Programs team at Expedia Group is looking for a Machine Learning Engineer III who mentors junior engineers, applies modern data engineering principles to improve existing systems, and leads complex, well-defined projects.

In this role, you will:

• Proactively collaborate with peers across the organization to build an understanding of cross-dependencies and shared problem-solving.

• Develop and test complex or non-routine software applications and related programs and procedures to ensure they meet design requirements.

• Apply knowledge of software design principles, data structures, design patterns, and computer science fundamentals to write clean, maintainable, optimized, and modular code with clear naming conventions.

• Contribute to design discussions for big data applications.

• Apply data manipulation techniques commonly used by Data Scientists.

• Coordinate with stakeholders holding varied perspectives to develop solutions and contribute your own suggestions.

• Think holistically to identify opportunities around policies and processes to increase efficiency across organizational boundaries.

• Assist with a whole-systems approach to analyzing issues, ensuring all components (structure, people, process, and technology) are identified and accounted for.

• Identify areas of inefficiency in code or system operations and offer suggestions for improvement.

• Recommend advancements, innovations, and changes in technologies—specifically relating to machine learning engineering, ML platforms, DS models, enterprise information management, business intelligence, and data science.

Experience and Qualifications:

• 3+ years of experience with end-to-end machine learning engineering pipelines in production environments (including feature engineering, model training, scoring, validation, etc.) and streaming applications in hybrid/cloud infrastructure.

• Bachelor’s or Master’s degree in a technical field or equivalent relevant work experience.

• Strong command of Spark, including understanding map-reduce, evaluating, optimizing, and debugging Spark applications.

• Proficiency with machine learning libraries such as PyTorch and TensorFlow, including common integration patterns for serving inference.

• Familiarity with data access, such as defining IAM policies for S3 buckets.

• Ability to instrument streaming or parallel inference tasks to accommodate large traffic or data volumes.

• Understanding and designing moderately complex systems.