Expedia Group aims to enhance the traveler experience across its brands by leveraging cutting-edge AI and machine learning technologies to improve Ranking, Recommendations, Text Search, and Traveler Insights. The goal is to optimize key business metrics such as click-through rate, conversion rate, and gross profit, while making travel more accessible and rewarding for people around the world.
Requirements
- Programming Proficiency: Comfortable programming in Python and Experience developing software in at least 3 languages, with a strong command of at least one language across multiple tech stacks; able to choose the right language for the task.
- Machine Learning Engineering: Built and maintained at least one end-to-end ML pipeline in production, covering feature engineering, model training, validation, and scalable inference.
- ML Libraries & Frameworks: Proficient in PyTorch, TensorFlow, and common patterns for model serving; familiar with dependency management in ML/DS systems.
- Big Data & Distributed Systems: Strong command of Spark (including map-reduce); experience training ML models on large datasets with GPUs or distributed compute.
- Cloud & Infrastructure: Experience of using cloud services (e.g. AWS). Experience with workflow orchestration tools (e.g. Airflow). Experience building streaming applications in cloud/hybrid environments; familiar with IAM policies and cloud storage (e.g., S3).
- Software Engineering Principles: Applies data structures, design patterns, and software frameworks to write clean, modular, maintainable code.
- Testing & Debugging: Designs testable systems, uses tools to monitor/debug code, and fixes issues within SLA constraints.
Responsibilities
- System & Software Design: Designs and develops moderately complex, testable, and observable systems; contributes to architectural discussions, especially for big data and ML applications.
- API & Service Development: Builds APIs and services for use across business units, ensuring reusability and scalability.
- Business Impact Alignment: Understands how technical work supports business goals; identifies and solves project-level business problems with minimal guidance.
- Innovation & Optimization: Identifies inefficiencies in code and systems; proposes improvements and innovations in ML engineering, platforms, and tooling.
- Operational Excellence: Ensures performance, scalability, and reliability of systems through monitoring, testing, and adherence to SLAs.
- Mentorship & Code Quality: Leads code reviews, mentors peers, and contributes to a culture of engineering excellence and best practices.
- Technical Communication: Documents and presents findings (e.g., RCAs or tech deep dives) clearly to both technical and non-technical audiences.
Other
- Bachelor’s or Master’s degree in Computer Science, Statistics, Math, Engineering, or related technical field; or equivalent related professional experience.
- 3+ years of experience in software engineering or machine learning engineering.
- Continuous Learning & Technical Breadth: Stays current with emerging technologies, seeks new skills, and shares knowledge across teams.
- Strategic Thinking: Applies systems thinking to identify process or policy improvements that scale beyond immediate teams or projects.
- Community Engagement: Participates in communities of practice, promotes shared learning, and fosters a culture of knowledge exchange.
