Sr./Staff Algorithm Engineer

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Sr./Staff Algorithm Engineer

Sr./Staff Algorithm Engineer

Location: Beijing, China

Didi Chuxing is the world’s leading mobile transportation platform. As a key drive of DiDi’s technology revolution, DiDi Big Data is committed to the development of state-of-the-art algorithms for real-life transportation applications. DiDi Big Data is looking for Sr./Staff Engineers with solid machine learning background, as well as the passion for changing the world and making transportation more pleasant. You will have the opportunity to work with world-class engineers and scientists, and design and develop core machine learning algorithms using DiDi’s enormous data.

Roles and Responsibilities 1. Design and implement core machine learning algorithms for order distribution, dispatching, carpooling, pricing, eco-engine, map services, user profiling, etc. 2. Design and implement machine learning models and algorithms for enhancing user experience for both drivers and riders, and establishing a better transportation network 3. Build highly efficient platforms for large-scale computation.

Qualifications 1. Master degree or above in Computer Science, Statistics, Math or related disciplines; 2. Hands-on experience on machine learning and data mining algorithms, including but not limited to LR, SVM, GBDT, Reinforcement Learning and Deep Learning; 3. Proficiency in large-scale data processing technology; experience of using Hadoop, Hive and Spark to analyze high-volume data sets; 4. Excellent programing skills (e.g., C++/ Python/Java/Scala); familiar with algorithms and data structure; 5. Passion for learning cutting-edge technology and industry trends on Artificial Intelligence; a strong record of publications in top artificial intelligence conferences and journals is a plus. 6. Excellent analytical and problem-solving skills and strong communication skills.

To apply, please send your resume+cover letter to: [email protected] with the email subject line: KDD_Name_Education_Sr./Staff Algorithm Engineer.

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