Recommender Algorithm Engineer
Job Description:
- Participate in optimizing video recommendations for a user base in the billions, improving core metrics such as dwell time, click-through rate, and retention rate.
- Engage in technical research and development in the fields of machine learning and deep learning, including but not limited to algorithm and system development related to deep model design and optimization, reinforcement learning, transfer learning, graph neural networks, etc.
- Analyze massive user behavior and video data, enhance effective features, mine user interests, and optimize sorting mechanisms.
- Utilize super-large-scale machine learning models and systems, employ advanced retrieval and ranking techniques, optimize the community ecosystem, and enhance the effectiveness of short video recommendations.
- Provide distributed algorithm implementation solutions for massive user behavior data, significantly improving algorithm computing scale and performance.
- Contribute to building recommendation system frameworks, providing high-concurrency, big data, efficient, and reliable online services.
- Participate in designing mechanisms for global traffic competition, assisting in expanding business boundaries.
- Engage in exploring and researching cutting-edge problems, provide comprehensive technical solutions tailored to practical application scenarios.
Qualifications:
- Master's degree or higher in Computer Science, Mathematics, Statistics, or related fields.
- Proficiency in Linux, C++, Java, or Python, excellent coding skills, solid foundation in data structures and algorithms.
- Knowledge in recommender systems, machine learning, data mining, or natural language understanding.
- Proficient in reading research papers, quick learner, strong analytical and problem-solving skills, excellent communication and collaboration abilities.
Bonus Points:
- Research or internship experience in fields such as recommender systems, machine learning, information retrieval, natural language understanding, computational advertising, or algorithmic game theory.
- Practical experience in developing and optimizing high-concurrency architectures in live online environments.
- Publication of papers in relevant top international conferences like SIGKDD, ICML, NIPS, WSDM, WWW, ACL, RECSYS.
- Experience in competitive programming competitions like ICPC, Topcoder Algorithm, or similar is a plus.