Machine Learning Engineer II ( Data engineering heavy) At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere. Introduction to team : Our Supply and Market Place division is sourcing the best possible inventory and content from our partners, generating the best prices and customer experience, and ensuring our supply is transacted fairly across our marketplace. This division builds innovative products, services, and tools to deliver high-quality experiences for partners and travellers both. The goal of Supply Coaching Foundation org is to delight partners by connecting them to the right travellers. We'll do that by building an adaptive experience that provides data and ML driven opportunities to our partners to help them grow their business. As part of NBA-Scout team we computes, organizes and streams the recommended actions for EG's supply partners with the ultimate goal of maximizing the returns for their time investment on Expedia Marketplace. Plus we also tracks partner's reactions to these recommendations to continuously learn & evolve. Our team works very closely with Machine Learning Scientists and Software Engineers in a fast-paced Agile environment to create and productionize algorithms that directly impacts the partners of Expedia. Along with this increased demand for creating new recommendations, we aim to build the NBA platform to make recommendation creation faster, easier, and more scalable. In this role, you will: Work in a cross-functional geographically distributed team of Machine Learning engineers and ML Scientists to design and code large scale batch and a few real-time data pipelines on the Cloud. Prototype creative solutions quickly by developing minimum viable products and work with seniors and peers in crafting and implementing the technical vision of the team Actively participate in all phases of the end-to-end ML model lifecycle (includes feature engineering, model training, model scoring, model validation) for enterprise applications projects to tackle sophisticated business problems in production environments Collaborate with global team of data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications Collaborate with cross-functional teams to integrate generative AI solutions into existing workflow systems. Participate in code reviews to assess overall code quality and flexibility. Passionate about simplifying systems, processes, and architecture while maintaining high quality and reliability. Define, develop and maintain artifacts like technical design or partner documentation Maintain, monitor, support and improve our solutions and systems with a focus on service excellence Minimum Qualifications: A degree in software engineering, computer science, informatics, or a similar field. 3+ years of professional experience with a Bachelor's degree, or 2+ years with a Master's degree. Must have experience in big data technologies, particularly Spark, Hive, and Databricks. Proficiency in Python and experience developing and deploying Batch and Real-Time Inferencing applications. Good understanding of prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and LLM orchestration frameworks. Preferred Qualifications: Experience programming in Scala. Hands-on experience with OOAD, design patterns, SQL, and NoSQL. A good understanding of machine learning pipelines and the ML Lifecycle. Experience integrating GenAI solutions with enterprise systems, APIs, and data platforms to solve business problems. Experience using cloud services (e.g., AWS) and workflow orchestration tools (e.g., Airflow). Familiarity with the basics of both traditional Machine Learning and Generative-AI algorithms and tools. Accommodation requests Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at id=job_accommodation. About Expedia Group Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading .