Student Researcher
ByteDance
About the Role
The Seed Infrastructures team works on distributed training, reinforcement learning frameworks, high-performance inference, and heterogeneous hardware compilation for AI foundation models. This is a project intern role with opportunities for short-term projects, real-world professional experience, and on-the-job learning.
Key Responsibilities
- Assist in building and optimizing large-scale distributed training systems (e.g., data/model parallelism, memory efficiency, reliability).
- Support the development and improvement of reinforcement learning training pipelines and post-training systems.
- Improve inference performance, including latency, throughput, and system stability.
- Contribute to compiler or runtime optimizations for GPU and other accelerators.
- Conduct performance analysis, profiling, benchmarking, and bottleneck identification.
- Develop internal tools and automation to improve infrastructure efficiency and developer productivity.
- Collaborate with researchers and engineers to translate model requirements into scalable system solutions.
Requirements & Tech Stack
- Proficiency in at least one programming language such as Python or C++.
- Familiarity with machine learning frameworks such as PyTorch or similar tools.
- Interest in pursuing long-term work in ML systems or AI infrastructure.
Qualifications
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical fields.
- Strong analytical and problem-solving skills.
- Ability to work collaboratively in a fast-paced technical environment.