Expedia Group
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Gurugram · On-site · 3-6 Yrs · 1 hour ago
Internet & Web Services · 10000+ Employees · Seattle, US
Expedia Group, Inc. (NASDAQ: EXPE) is the global travel marketplace with one purpose: to help travelers explore the world, one journey at a time. Expedia Group™ connects travelers, partners, and advertisers through its trusted brands, leading technology, and rich first-party data, delivering predictive, personalized experiences that shape the future of travel. Expedia Group’s ecosystem includes three flagship consumer brands – Expedia®, Hotels.com®, and Vrbo® – the largest B2B travel business, and a premier advertising network. Guided by an experienced and passionate global team, Expedia Group helps millions of travelers in more than 70 countries explore the world with confidence and ease.
Hiring: Engineering
What employees say
+ Excellent work environment, employee centric policies, best salary in travel domain
− None as of now from Senior Management
More reviews on the company profile.
Interview experience · MLE intern
In the interview they asked -> MLE > asked about project and gave situation based problems like book recommendation ->DSA hard DP , 2pointer problems ->Behavioral Questions ->HR Round ->they asked ab
Difficult difficulty · Bengaluru · 266 reports
More interview insightsJob description
Overview
Machine Learning Engineer II ( Data engineering heavy)
Responsibilities
- 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
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.
- Hands-on experience with OOAD, design patterns, SQL, and NoSQL.
- A good understanding of machine learning pipelines and the ML Lifecycle.
- Familiarity with the basics of both traditional Machine Learning and Generative-AI algorithms and tools.
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Job application FAQ
Last updated 15 September 2026
- How do I apply for Machine Learning Engineer II ( Data engineering heavy) | Gurgaon, IN at Expedia Group?
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- Is Machine Learning Engineer II ( Data engineering heavy) | Gurgaon, IN remote or on-site in Gurugram, Haryana?
- This listing is marked on_site with location Gurugram, Haryana. Confirm details on the job description before applying.
- What skills matter for this Machine Learning Engineer II ( Data engineering heavy) | Gurgaon, IN role at Expedia Group?
- This is a mid-level Machine Learning Engineer II ( Data engineering heavy) | Gurgaon, IN role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.