Software Engineer, Large Model System Graduate (Machine Learning Sys-US) - 2026 Start (BS/MS)

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at ByteDance.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

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.

The Applied Machine Learning - Machine Learning Systems team provides E2E machine learning experience and machine learning resources for the company. The team builds heterogeneous ML training and inference systems based on GPU and advanced chip technology and advances the state-of-the-art of ML systems technology to accelerate models such as stable diffusion, language modeling and multi-modality models. The team is also responsible for the research and development of hardware acceleration technologies for cloud computing, via technologies such as distributed systems, compilers, HPC, and RDMA networking. The team is reinventing the ML infra for large-scale language models.


Responsibilities
- Responsible for the machine learning system development of the company's large-scale models, researching new applications and solutions of related technologies in areas such as search, recommendation, advertising, content creation, conversation, and customer service, meeting the growing demand for intelligent interaction from users, and comprehensively improving users' lifestyles and communication methods in the future world.

The main work directions include:
- Responsible for the design and development of the architecture of large-scale machine learning systems, solving technical difficulties such as high concurrency, high reliability, and high scalability of the system.
- Covering various sub-directions of machine learning system, including resource scheduling, model training, model inference, data management, and workflow
- Iterate and develop the system using customer-driven scenarios.

The base salary range for this position in the selected city is $112725 - $177840 annually.