We have eight employee resource groups: WELL, Asian Community at Expedia Group (ACE), Ability Inclusion Movement (AIM), Black Expedia Allied Movement (BEAM), Expedia Veterans and Friends and Family (EVFF), Indigenous Diversity, Expedians and Allies (IDEA), Latinx at Expedia and Allies for Development (LEAD) and PRIDE for our LGBTQIA+ employees and allies.

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Expedia

We offer parental leave as well as maternal and new mother support. Wellness rooms are provided for employees&rsquo; wellness needs, such as nursing mothers, in our global offices. Our fertility benefits allow employees and their partners to preserve their fertility, including single parents and LGBTQIA individuals and couples. We also offer an Adoption Reimbursement Program to help employees with expenses and travel related to the adoption process.
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At Expedia Group, we&rsquo;re always learning and always growing &mdash; both on the job and off. To encourage additional learning, we offer reimbursement for advanced education courses you take that are related to your current position.

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Are you passionate about technical leadership in an engineering team that uses machine learning and data to build a platform for crafting intelligent Virtual Agents that is helping to drive thefuture of a multi-billion-dollar business?As a Sr Engineer within the Conversation Platform Technology team, you will provide technical leadership and mentorship to a team dedicated to driving technology innovation. The capabilities and solutions that emerge from your work will extend ongoing work in the areas of deep understanding of natural language, question answering, policy learning for determining the next action in conversations, and surfacing personalized insights. You will beenabling groups across the company to create outstanding Virtual Agent experiences worldwide in Expedia Group apps, web sites, social channels, and voice channels!We support hundreds of millions of conversations a year across a global brand portfolio and partnership programs. Our team is building out the platform's intelligence services that power Expedia Group's Virtual Agents to address customer needs in an optimal manner without needing human intervention. In this role, with your technical experience along with mentorship and inspiring others, you will build frameworks, services, data sets, and models that drive self-service and customer loyalty up, and customer effort down at Expedia, enabling millions of travelers to enjoy their flawlesstrip!What you’ll do:<ul><li style="text-align: justify;">You can extend outside of the direct organization and collaborate with peers across a senior level organization.</li><li style="text-align: justify;">You will serve as a guide to others by sharing and helping junior associates in their duties.</li><li style="text-align: justify;">You will design optimal ML model interface for feature input and model inference output for integration with application engineering solution and optimize for functional and operational requirements.</li><li style="text-align: justify;">You will creatively test and maintain ML software applications and related programs and procedures by using a variety of software development tools following design requirements of customer and advise on technical limitations of software design for products and provide alternative solutions.</li><li style="text-align: justify;">You will take a whole systems approach to analyze issues and implements holistic solutions by ensuring that linkages between structure, people, process and technology are made.</li><li style="text-align: justify;">You will design and lead advancements, innovations and changes in current solution designs relating to latest advancements in software engineering (specifically relating to machine learning engineering, ML platforms, DS models, enterprise information management, business intelligence and data science).</li><li style="text-align: justify;">You will report on status of difficult or high-level projects to local tech leadership through written or oral means. Ensure documentation is complete.</li></ul>Who you are:<ul><li style="text-align: justify;">Bachelor's, Master's, PhD in Computer Science or Engineering; or equivalent related professional experience.</li><li style="text-align: justify;">Relevant experience includes:</li><li style="text-align: justify;">Worked in at least in 2 multi-quarter projects.</li><li style="text-align: justify;">Worked in decentralized teams and projects.</li><li style="text-align: justify;">Formally mentored at least 3 individuals.</li><li style="text-align: justify;">Drove technical design end-to-end of at least 3 machine learning projects.</li><li style="text-align: justify;">Contributed to the machine learning community through a blog post, open-source contribution, tech talks, etc.</li><li style="text-align: justify;">Built and maintained more than one machine learning engineering pipeline end-to-end in production environments (includes feature engineering, model training, model scoring, model validation, etc.)</li><li style="text-align: justify;">Strong in multiple technologies or languages and can justify technology choices to technical and non-technical observers.</li><li style="text-align: justify;">You serve as an expert for a given domain, make well-defined technology choices and mentor other engineers.</li><li style="text-align: justify;">You create team project systems and guide integrations across teams within business unit.</li><li style="text-align: justify;">You understand highly complex systems and design moderately complex systems.</li><li style="text-align: justify;">Ability to identify and advocate for project quality using testing, monitoring and alerting at the project level.</li><li style="text-align: justify;">You can establish operational excellence metrics at the team level and guide others in design of easily testable and observable software.</li><li style="text-align: justify;">You can create new tools or patterns that improve the ability to process data at EG.</li><li style="text-align: justify;">Active in the design for the feature store or model registry, you are familiar with the latest tools in MLOps, such as KubeFlow, AWS Sagemaker, MLFlow, etc. and can guide teams whether to use them or not.</li><li style="text-align: justify;">Familiar with the latest research and tools in machine learning, you can advise and suggest particular model types/neural network topologies for a particular domain.</li><li style="text-align: justify;">Familiarity with tradeoffs with different model approaches. e.g. Advocate using distilBERT instead of BERT is certain cases.</li><li style="text-align: justify;">Strong understanding of how team's goals fit a business need.</li><li style="text-align: justify;">Ability to identify business problems at the team level and provide solutions</li></ul>

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