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Senior Manager, Machine Learning Engineering

United States - Washington - Seattle


Senior Manager, Machine Learning Engineering

Are you an engineering manager who embraces servant leader principles?  Are passionate about technology and leadership in equal measures?  Do you relish the challenge of working in a large scale and fast-moving technology company leading teammates around the world?  Are you fascinated by data and AI and building robust machine learning products which process massive amounts of data at scale and speed to provide crucial insights to the end customer?

This is exactly what we, the Machine Learning Engineering group in Expedia, do.  Our mission is to partner with our Data Science counterparts to use AI/ML to collaboratively transform Expedia’s data assets into intelligent and real-time insights for our customers. We work on creating AI services and deploying machine learning models and products to support a variety of applications which are used by 1000+ market managers, analysts, external hotel 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, AWS and much more! 

We are looking for a passionate, creative, and innately curious senior engineering manager to join our Conversational AI/ML Engineering team.  The goal of our team is to accelerate the conversation platform virtual agent capabilities through AI thereby increasing the ability for our customers and partners to self-serve, reducing the need for live agent contacts and providing a user experience with a high net promoter score. Our team is involved in building Conversational AI capabilities which include deployment of generalized and/or domain specific NLU models such as intent classification, named-entity recognition, sentiment analysis, etc. that can support multiple brands, products, and languages at scale.  Our ML Engineering team is also responsible for building automated model generation APIs to accelerate model training, deployment, evaluation, active learning, and continuous performance improvements.

As a Senior Engineering Manager, you will be involved in all aspects of software development for your team, including participating in technical designs, implementation, functional analysis, and release for mid-to-large sized projects.  You will also be responsible for on-time delivery of features, setting timelines, coaching, and mentoring your team and hiring and recruiting. 

What you’ll do:

  • You will lead implementation teams and ensure the successful execution of new ideas or approaches

  • You will find opportunities for multi-disciplinary collaboration such as with data engineers, data science and machine learning

  • You will determine different phase milestones and priorities in collaboration with product management and data science peers

  • You will extend outside of the direct organization and collaborate with peers across a senior level organization

  • You will partner with the business to have a clear understanding of how the technology stack is tied to business outcomes and our bottom line

  • You will creatively test and maintain software applications and related programs and procedures by using a variety of software development tools following design requirements of customer

  • You will act as a spokesperson for software design best practices and assist with any component or issue within the software development life cycle

  • You will research and recommend frameworks and architectural/code design patterns and identify areas of improvement within the code and suggests solutions

  • You will advocate for operational excellence (such as unit testing, establishing SLAs, programming for resiliency and scalability) and utilize knowledge in Expedia Group's languages, frameworks, cloud services, toolkits, methodologies

  • You will examine inefficiencies in the existing stack operation and encourage engineers to improve them

  • You will review the skill and expertise requirements to accomplish team goals and identify staffing and talent resources to fill project roles

  • You will develop action plans for optimal resource utilization and manage resource usage among team

  • You will evaluate the full complement of team talent, identify gaps, and implement action plans to fill gaps and drive achievement of goals

  • You will develop a diverse talent pipeline for a team, including onboarding, and evaluating talent gaps and opportunities

  • You will craft the culture of the team by building team rituals, processes and practices that build strong team bonds; create an open, trusting environment where diverse viewpoints, opinions, approaches, candid conversations, and critiques can happen

  • You will coordinate and contribute to the process and practice that drive cross-functional operational excellence

  • You will actively build space for feedback and contribution from the team to improve EG’s Machine Learning culture and practice

Who You Are:

  • Bachelor's, Master’s or related technical field; or Equivalent related professional experience

  • Relevant Experience:

    • Recruited at least 5 machine learning engineers to own team

    • Performance managed at least 3 individual contributors

    • Executed capacity planning/allocation of teams of 10 or more

    • Managed individuals in different locations

    • Led more than 3 multi-quarter machine learning engineering projects in close collaboration with data science, product, and engineering 

  • Strong business acumen experienced in defining team goals and how they fit a business need across multiple teams working together and delivering solutions to business problems spanning teams

  • Experience in delivering and influencing product roadmap, working in collaboration with product team

  • Demonstrate strength with multiple technologies or languages

  • Able to justify technology choices to technical and non-technical observers

  • Has been responsible for multiple technical domains

  • Demonstrates an ability in making well-defined technology choices

  • Experience in designing and implementing Big Data/ML applications (data ingestion, real-time data processing and batch analytics) in Spark Streaming, Kafka, Hadoop

  • Strong experience with cloud computing platforms (AWS, EMR, Kubernetes, Docker)

  • Experience with microservice architecture and design

  • Experience on Hadoop-ecosystem technologies in particular MapReduce, Spark, Hive, YARN

  • Experience working on any one distributed database system like Hadoop (Hive/HDFS), Qubole/Databricks/Amazon EMR etc.

  • Ability to lead multiple simultaneous projects, prioritize effectively and thrive in a fast-paced, dynamic environment

  • Preferred - Experience on machine learning toolkits like spark mllib, H20, scikit-learn, R and ML techniques

  • Preferred – Experience working on chatbot/conversation platforms and working knowledge of NLU and NLP concepts and models


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®,®, Expedia® Partner Solutions, Vrbo®, Egencia®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®,™, and Expedia Cruises™.  

© 2021 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50

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, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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Job Category
Technology Group

Job Function

United States - Washington - Seattle

Job Type
Full-Time Regular

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