Applied Scientist Intern

The System Technology and Engineering (STE) team, has been committed to the development and research of infrastructure system technologies, such as operating system kernel, various virtualization technologies (Cloud Native, SDN, NFV), performance optimization of system software and libraries, stability and reliability of large-scale data center, collaborative design of next-generation hardware and software, etc. We actively participate in open-source communities and incorporate cutting-edge technology and innovation into our products. We are looking for talented individuals to join us for an internship in 2025. Internships at ByteDance aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at ByteDance. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to ByteDance and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities: - Collaborate closely with team members from diverse fields to deeply understand the data and the context of challenges in next-generation hardware and software design. - Design, implement, and evaluate state-of-the-art solutions to large-scale optimization problems. - Utilize innovative and critical thinking, actively implement your ideas in daily tasks. - Stay updated on recent advancements and actively discuss and share insights with team members. Minimum Qualifications: - Currently pursuing a Bachelor's or Master's degree in Applied Mathematics, Electrical Engineering, Computer Science, or a related area. - Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment. - Familiar with ML/DL techniques, algorithms and frameworks like PyTorch or TensorFlow. - Proficiency in Python. Preferred Qualifications: - Strong background in one of the following fields: Graph Theory, Non-Convex Optimization, Operations Research, Computational Mathematics, Reinforcement Learning. - Interest or experience in hardware design. - Experience in AI model development, training, evaluation and deployment on Cloud, Cluster or on-premises. - Experience with development applications with C++ and CUDA programming. - A strong sense of responsibility, coupled with exceptional communication and teamwork skills.