ML Research Intern – Travel Tech & Real-World Impact

Expedia, Inc.; San Jose (CA); Hybrid; USD 51,000 - 84,000; Full time

Benefits offered by this job

Health benefits

Hybrid work policy

Relocation support

Travel discounts

Job summary

Expedia Group is offering a Global Summer Internship in Applied Science. You’ll work with a team of ML scientists to prototype models, design experiments, and translate data insights into production-ready features.

Expect hands-on learning, mentorship, and exposure to real business priorities while building your network within Expedia Group. Successful candidates will engage in role-specific technical and professional learning, with a mix of in-person and virtual sessions, and may contribute to

Qualifications

• Must be available to commit to the full program dates.
• Must be graduating with a PhD in a technical subject between Dec 2027 and Jul 2028.
• Must relocate to the job city if outside commuting distance.
• Must have Python and/or Scala, SQL knowledge.
• Helpful to have knowledge of distributed file systems and Spark/Hadoop.

Responsibilities

• Design, prototype, and evaluate ML models under guidance of senior scientists.
• Implement maintainable model training and inference code with unit tests.
• Collaborate with data scientists, engineers, and product partners to define success metrics.
• Analyze data and perform feature engineering to improve model quality and fairness.
• Explore AI-enabled solutions and safely integrate ML workflows into production.

Skills

Python

SQL

Scala

Java

R

C++

Hive

Hadoop

Spark

AWS

Education

PhD in technical/analytical field

Tools

Spark

Hadoop

AWS

Job description

Expedia Group is offering a Global Summer Internship in Applied Science. You’ll work with a team of ML scientists to prototype models, design experiments, and translate data insights into production-ready features.

Expect hands-on learning, mentorship, and exposure to real business priorities while building your network within Expedia Group. Successful candidates will engage in role-specific technical and professional learning, with a mix of in-person and virtual sessions, and may contribute to