AI Infrastructure Intern: Foundation Models & Training

ByteDance; San Jose (CA); On-site; USD 63,000 - 89,000; Full time

Job summary

ByteDance Seed Infrastructure Intern role focuses on distributed training, RL framework work, high-performance inference, and compiler/runtime optimizations for AI foundation models. You will contribute to large-scale systems and gain hands-on experience in a fast-paced environment.

As an intern, you’ll tackle projects across training systems, RL pipelines, and performance improvements for GPUs and accelerators, collaborating with researchers and engineers to translate model needs into scalable

Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical fields.
• Proficiency in at least one programming language such as Python or C++
• Familiarity with machine learning frameworks such as PyTorch or similar tools
• Strong analytical and problem-solving skills
• Ability to work collaboratively in a fast-paced technical environment
• Interest in pursuing long-term work in ML systems or AI infrastructure

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

Skills

Python

C++

PyTorch

Education

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical fields

Job description

ByteDance Seed Infrastructure Intern role focuses on distributed training, RL framework work, high-performance inference, and compiler/runtime optimizations for AI foundation models. You will contribute to large-scale systems and gain hands-on experience in a fast-paced environment.

As an intern, you’ll tackle projects across training systems, RL pipelines, and performance improvements for GPUs and accelerators, collaborating with researchers and engineers to translate model needs into scalable