Co-Op: Machine Learning Application Developer

23 hours ago


Pasco, Washington, United States Rakuten Group, Inc. Full time

Rakuten Group, Inc. is at the forefront of AI and Data initiatives, playing a pivotal role in enhancing the user experience and operational efficiency across our diverse portfolio. Our Technology Services Division is dedicated to developing cutting-edge services in areas such as Search, Recommendation, Advertising and Marketing Optimization, Inventory and Price Optimization, Data and Analytics, Conversation AI, and Rakuten AI for Business.

Job Description

This is a co-op position designed for college students passionate about AI and Data Science. The successful candidate will have the opportunity to apply their academic knowledge to real-world challenges, gain hands-on experience, and contribute to pioneering AI and Data projects within Rakuten.

Responsibilities include developing predictive models on large-scale datasets using statistical modeling, machine learning, and analytics techniques, collaborating with product management and engineering groups to develop new products and features, assisting in testing and validating AI model performance, and addressing any issues or bottlenecks in the software.

Qualifications

The ideal candidate should have a good understanding of statistical modeling, machine learning, deep learning, or data analytics concepts, proficiency in one or more programming languages such as Python, Java, and C, and familiarity with one or more machine learning or statistical modeling tools.

In addition, they should possess strong analytical and quantitative problem-solving ability, excellent communication (written and verbal) skills, collaboration skills, and the ability to prioritize tasks to meet deadlines and work independently and collaboratively in a team.

Benefits

Rakuten Group, Inc. offers equal employment opportunities to all employees and applicants for employment, prohibiting discrimination and harassment of any type. We consider applicants for employment without regard to race, color, religion, age, sex, national origin, disability status, genetic information, protected veteran status, sexual orientation, gender, gender identity or expression, or any other characteristic protected by federal, state, provincial or local laws.



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