Senior Data Engineering Lead

2 weeks ago


Gurgaon, Haryana, India Expedia Group Full time

Expedia Group: Senior Machine Learning Engineer

At Expedia Group, we're in the business of helping travelers make their next trip easier and more enjoyable. We're looking for a Senior Machine Learning Engineer to join our team and help us build innovative solutions that make a real difference in people's lives.

This role will be part of our Machine Learning Engineering group, which partners with our Machine Learning Science counterparts to use AI/ML to collaboratively transform Expedia's data assets into intelligent and real-time insights. Our mission is to support a variety of applications used by 1000+ market managers, analysts, our supply partners, and our travelers.

What You'll Do:

  • Lead the design and development of large-scale batch and real-time ML Services
  • Design, implement, and deploy large-scale data pipelines (both real-time and batch) and back-end services
  • Lead the end-to-end product life cycle for mid-to-large machine learning/data engineering projects: design, development, model validation/testing, model deployment, and providing operational excellence and support
  • Find and advocate for industry standards and best practices in machine learning engineering methodologies, techniques, and technologies
  • Contribute to advancing the team's design methodology and quality programming practices and mentor junior team members to adapt best practices
  • Innovate and implement new ideas to solve complex software problems and prototype creative solutions to enable product MVPs
  • Independently understand scheduling, cost constraints, and impact to other teams; and make resource and architectural trade-offs based on those factors
  • Anticipate and prevent problems and roadblocks, before they occur, and present technical issues and their impact to leadership
  • Lead, coordinate, and collaborate on multiple concurrent and complex cross-organizational initiatives
  • Effectively build and maintain a network of key contacts across the company, and leverage these contacts to achieve results
  • Communicate and work effectively with geographically distributed cross-functional teams

Who You Are:

  • Bachelor's or Master's degree in software engineering, computer science, informatics, or a related technical field; or equivalent related professional experience
  • 8 to 10+ years of work experience in software engineering
  • 4+ years of experience in designing and implementing Big Data/ML applications (data ingestion, real-time data processing, and batch analytics) in Spark Streaming, Kafka, Hadoop
  • Experience on Hadoop-ecosystem technologies in particular MapReduce, Spark, Hive, YARN
  • Experience in productionizing machine learning models including feature engineering, model scalability, model validation, and model deployment
  • Solid server-side programming skills in multiple languages (Scala/Java and Python), and hands-on experience in OOAD, design patterns, NoSQL, and SQL
  • Strong experience with cloud computing platforms (AWS, EMR, Kubernetes, Docker)
  • Strong experience working with ML platforms (Databricks, SageMaker, etc.)
  • Solid knowledge in SQL (T-SQL/PL-SQL), ETL, and data modeling
  • Experience with microservice architecture, and design
  • Experience on machine learning toolkits like Spark MLlib, H20, scikit-learn, R, and ML techniques
  • Strong command with machine learning libraries such as PyTorch and TensorFlow and knowledge of common integration patterns for serving inference with them
  • Familiar with training models with very large datasets- strategies for parallelizing and optimizing the training jobs especially with GPUs or large compute
  • You have hands-on experience with workflow management tools (e.g. Airflow)
  • Familiar with machine learning inference at scale. Can instrument streaming or parallel inference tasks to accommodate large traffic or volume of data
  • Experience working with Agile/Scrum methodologies
  • Experience on Recommender Systems is a plus
  • Familiarity with the e-commerce or travel industry


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