Software Engineer Intern (Applied Machine Learning-Enterprise) - 2026 Start (PhD)

The Applied Machine Learning Enterprise team combines system engineering and machine learning to develop and operate a big model service platform that offers businesses Model-as-a-Service solutions (MaaS) to both the big model vendors and users.

We are actively seeking talented Software Engineers specializing in Large Language Models (LLM) to join our team.

We are looking for talented individuals to join us for an internship in 2026.

Internships at ByteDance aim to offer students industry exposure and hands-on experience.

Watch your ambitions become reality as your inspiration brings infinite opportunities at ByteDance.

PhD internships at ByteDance 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).

Responsibilities: - Building a next-generation big model as a service platform to serve hundreds of LLMs based applications; - To develop and maintain the big model as a service platform, including offline training/finetuning, online inference, model management, and resource orchestration, etc.; - To manage a huge number of GPU resources and provide computing power efficiently.

Minimum Qualifications: - Currently pursuing a PhD in Computer Science or related technical field; - Proficient in deep learning frameworks such as PyTorch or TensorFlow; - Experience with software development in at least one of the following programming languages: C++, Python, Go; - Good sense of teamwork and communication skills, practical experience in relevant business scenarios is preferred; - Strong software programming capabilities, exhibits good code design and coding style;

Preferred Qualifications: - Experience in NLP and LLM technologies; - Experience or research in Alignment for Large language models; - Experience in ModelOps, for example large model management, finetuning workflow management, etc.; - Contribution to top-tier conference papers, including NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, KDD, etc. is a big plus.

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