Machine Learning Engineer II
Expedia · Gurugram · 3+ yrs experience · Posted 2026-07-24
Tech stack: Java, Python
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About the role
Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
This Machine Learning Engineer role is part of the Distribution & Supply team which sits within our Technology division. The Distribution & Supply team builds and optimizes the machine learning–driven systems that power how our travel supply is connected, priced, and surfaced across Expedia Group’s global marketplace, ensuring partners can efficiently reach travelers with the right inventory at the right time. In this role, you will apply advanced machine learning engineering to design, deploy, and scale robust models that directly improve the quality and performance of our distribution platform for both travelers and partners.
Responsibilities:
- Design and implement scalable machine learning solutions across multiple domains, ensuring technical rigor and robust architecture.
- Develop and deploy machine learning models, including data preprocessing, feature engineering, and model evaluation.
- Collaborate cross-functionally to integrate ML systems with existing products and services, promoting technical excellence and innovation.
- Drive system design, including low-level design (LLD), API design, and data modeling to support real-time and batch ML workflows.
- Safely integrate and operate AI/ML-enabled solutions that improve outcomes, leveraging modern AI/ML concepts and best practices.
- Contribute to technical discussions, code reviews, and knowledge sharing to foster a culture of continuous improvement and high-quality software delivery.
- Experience and
Qualifications:
- Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
- 3+ years of relevant professional experience.
- Demonstrated ownership of end-to-end machine learning projects, from data exploration through model deployment in production.
- Proficiency in programming languages such as Python or Java, and experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products
- Preferred
- Experience operating machine learning solutions at scale, with an emphasis on reliability, performance, and maintainability.
- Experience in designing and implementing ML systems within multi-service environments.
- Proven ability to implement automated monitoring, testing, and retraining pipelines for ML models.
- Demonstrated expertise in integrating AI/ML capabilities into large-scale applications, ensuring responsible use of data and model outcomes.
- Knowledge of responsible AI practices, including model fairness, interpretability, and compliance within product environments.
Qualifications
- Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
- 3+ years of relevant professional experience.
- Demonstrated ownership of end-to-end machine learning projects, from data exploration through model deployment in production.
- Proficiency in programming languages such as Python or Java, and experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products
- Experience operating machine learning solutions at scale, with an emphasis on reliability, performance, and maintainability.
- Experience in designing and implementing ML systems within multi-service environments.
- Proven ability to implement automated monitoring, testing, and retraining pipelines for ML models.
- Demonstrated expertise in integrating AI/ML capabilities into large-scale applications, ensuring responsible use of data and model outcomes.
- Knowledge of responsible AI practices, including model fairness, interpretability, and compliance within product environments.
Responsibilities
- Design and implement scalable machine learning solutions across multiple domains, ensuring technical rigor and robust architecture.
- Develop and deploy machine learning models, including data preprocessing, feature engineering, and model evaluation.
- Collaborate cross-functionally to integrate ML systems with existing products and services, promoting technical excellence and innovation.
- Drive system design, including low-level design (LLD), API design, and data modeling to support real-time and batch ML workflows.
- Safely integrate and operate AI/ML-enabled solutions that improve outcomes, leveraging modern AI/ML concepts and best practices.
- Contribute to technical discussions, code reviews, and knowledge sharing to foster a culture of continuous improvement and high-quality software delivery.
- Experience and