Machine Learning Internship

Bringle Academy Machine Learning Intern

Stop Thinking Keep Bringling !!

Bringle is the largest travel site in the world. We get millions of unique visitors on a monthly basis.

Do you want to apply your machine learning expertise to find solutions for the largest travel site on the web? Do you get excited about the prospect of working with not just big data, but huge data? Would you like to work across diverse areas including personalization, fraud detection, and natural language processing?

Bringle Academy’s Machine Learning team to works on machine learning and statistical analysis problems across several groups in the company. As a member of this group you’ll use these techniques to implement new solutions and improve existing approaches to large scale data analysis. You’ll be relied upon to research, design, and implement your projects. You must be comfortable communicating your approach to project managers across the company.

**Responsibilities

• Working with Hadoop, Redshift, and other big data systems

• Applying machine learning techniques to personalize the site experience for our users
• Building algorithms to help our review fraud team catch bad guys
• Working on various classification and regression problems over our huge database of traveller reviews and site data

**Requirements

• Working towards a Bachelors or Master’s Degree in Computer Science, Computer Engineering, Math or a related field. Advanced degree preferred.

• A passion for solving real world problems with machine learning

• Experience working with collaborative filtering, clustering, classification, regression, and/or statistical modeling.

• Knowledge of Hadoop, Hive, Redshift or other big data tools

• Knowledge and experience of SQL and relational databases

• Fluency with statistical tools such as R or Python scikit-learn

• Proficiency in Java or C++

• Strong computer science fundamentals (data structures and complexity)

All your information will be kept confidential according to EEO guidelines.