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Machine Learning Engineer II:
Are you fascinated by machine learning and building robust machine learning pipelines which process massive amounts of data at scale and speed to provide crucial insights to the end consumers?
This is exactly what we, the Machine Learning Engineering group in Expedia, do. Our mission is to partner with our Machine Learning Science counterparts to use AI/ML to collaboratively transform Expedia’s data assets into intelligent and real-time insights to support a variety of applications which are used by 1000+ market managers, analysts, our supply partners, and our travelers. Our work spans across a variety of datasets and ML models and across a diverse technology stack ranging from Spark, Sagemaker, Airflow, Databricks, Kubernetes, AWS and much more!
What you will do:
Work in a cross-functional team of Machine Learning engineers and Data scientists to design and code large scale batch and real-time data pipelines on the AWS.
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
Communicate and work effectively with geographically distributed cross functional teams
Participate in code reviews to assess overall code quality and flexibility
Resolve problems and roadblocks as they occur with peers and help unblock junior members of the team. Follow through on details and drive issues to closure
Define, develop and maintain artifacts like technical design or partner documentation
Drive for continuous improvement in software and development process within an agile development team
Participate in user story creation in collaboration with the team
Support and troubleshoot data and/or system issues as needed
Who you are:
Degree in software engineering, computer science, informatics or a similar field.
Comfortable programming in Scala, or Java and have hands-on experience in OOAD, design patterns, SQL and NoSQL.
Knowledgeable in Hadoop-ecosystem technologies, in particular Hadoop, Hive, and Spark.
Passionate about learning, especially in the areas of microservices, design patterns, system architecture, Data Science and Machine Learning.
Experience of using cloud services (e.g. AWS)
Experience working with Agile/Scrum methodologies.
Nice to have:
High-level understanding Machine learning pipelines
Experience with Python.
Experience with machine learning frameworks such as TensorFlow
Experience in crafting real-time streaming applications, preferably in Spark, and Kafka/KStreams.
Familiar with workflow management tools (e.g. Airflow)
Familiar with the e-commerce or travel industry.
About Expedia Group
Expedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™.
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Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals to whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.
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.