Student Researcher - (Seed Model - AI Foundation Models Infrastructure) - 2026 Start (PhD)

About the role

The Seed Infrastructures team oversees the distributed training, reinforcement learning framework, high-performance inference, and heterogeneous hardware compilation technologies for AI foundation models. We are looking for talented individuals to join us for an internship in 2026. PhD internships at our Company aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Established in 2023, the ByteDance Seed team is dedicated to pioneering new paths toward artificial general intelligence. We aspire to advance the frontier of intelligence to drive progress for both technology and society. With a long-term vision for the AI sector, the Seed team's research spans MLLM, GenMedia, AI for Science, and Robotics. We maintain a global presence with laboratories and career opportunities across China, Singapore, and the United States. To date, we have launched industry-leading general foundation models and cutting-edge multimodal capabilities. Our technology powers over 50 application scenarios — including Doubao, Jimeng, TRAE, Dola and Dreamnia — and serves enterprise customers through Volcano Engine and BytePlus. Third-party data shows that the Doubao App ranks first in user volume in the Chinese market, while Doubao foundation models lead the industry in average daily token consumption.

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day. As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Responsibilities

• Design and optimize large-scale distributed training systems (e.g., data/model/pipeline parallelism, memory efficiency, fault tolerance)
• Contribute to reinforcement learning training frameworks and large-scale post-training systems
• Improve inference performance, latency, and throughput for foundation models
• Develop compiler or runtime optimizations for heterogeneous hardware (GPU/accelerator)
• Work on system-level performance analysis, profiling, and bottleneck diagnosis
• Build tooling and automation to improve developer productivity and system reliability

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD degree in Computer Science, Electrical Engineering, or related technical fields
• Strong programming skills in Python and/or C++
• Solid understanding of systems, distributed computing, machine learning systems, or performance optimization
• Experience with one or more of the following:
• Distributed training frameworks (e.g., PyTorch FSDP, Megatron-style parallelism)
• Reinforcement learning training systems
• GPU programming (CUDA, Triton) or compiler technologies

Preferred Qualifications:

• Experience working on large-scale ML systems or infrastructure projects
• Contributions to open-source ML systems or performance tooling
• Publications in ML systems, distributed systems, or related areas (a plus but not required)

Benefits

• Day one access to health insurance, life insurance, wellbeing benefits and more
• 10 paid holidays per year
• Paid sick