Tencent is looking for a Machine Learning Research Engineer Internship #EngineerJobs #InternshipJobs #ResearchJobs
Work Mode: Onsite Responsibilities: In the era of technology disruptions slowly changing how the world works, digitalization transforms the way of working, how we socialize with others and casts in many other facets a meaningful impact on all. Tencent as an internet company, uses technology to enrich the lives of internet users, and assist the digital upgrade of enterprises. At Tencent, we adhere to the mission we believe, embed it into our day to day work – Value for Users, Tech for Good. WeiXin Group(WXG) is responsible for the construction and operation of the Weixin ecosystem and leveraging Weixin’s open platforms such as Official Accounts, Mini Programs, Weixin Pay, WeCom and search function. WXG provides solutions and connectivity for intelligent upgrades across all industries. WXG is also responsible for the development and operation of QQ Mail, WeRead and other products. 1. Understand Tencent’s data and be responsible for the analysis and mining of massive amounts of data, constructing user profile models in multiple business areas; 2. Responsible for the development of machine learning algorithms and models (particularly in the field of deep learning), including but not limited to: neural network model design, hyperparameter optimization, and experimentation with various learning and optimization methods; 3. Accelerate the distributed implementation of existing algorithms and models for business units, and enrich the company’s internal public parallel algorithm library; 4. Explore and research cutting-edge issues in machine learning, especially deep learning, in combination with future practical application scenarios, and provide comprehensive technical solutions; 5. Provide model support in the fields of computer vision, speech recognition, natural language processing, and precision recommendation, and carry out innovative application experiments and product development. Requirements: 1. Candidates should have a Ph.D. or outstanding master’s degree in computer science, information engineering, pattern recognition, artificial intelligence, automation, software engineering, electronic engineering, statistics, applied mathematics, physics, information security, signal and information processing, or related fields; 2. Should be familiar with commonly used machine learning algorithms, especially in areas such as deep learning and reinforcement learning. Must have a solid foundation and deep understanding of pattern recognition, probability, statistics, optimization algorithms, and a strong interest in their principles and applications; 3. Proficient in at least one programming language, such as C/C++, Java, or Python, with strong hands-on skills. Should have knowledge of one or more machine learning or deep learning frameworks, such as Spark, XGBoost, Caffe, TensorFlow, etc.; 4. Willing to get hands-on experience, possessing good logical thinking skills and sensitivity to data. Must be able to read and write academic papers in English fluently and have excellent research ability to learn new technologies.