Software Engineer Intern – Large Language Models (LLM)

Job Description

Research Scientist Intern (Applied Machine Learning-Enterprise) – 2026 Summer (BS/MS) | ByteDance

The Tone:
This is an internship at ByteDance, a global technology company founded in 2012 with a mission to inspire creativity and enrich life through products like TikTok, Lemon8, and CapCut. This role is within the Applied Machine Learning Enterprise team, which combines system engineering and machine learning to develop and operate a big model service platform. The team creates Model-as-a-Service (MaaS) solutions for both big model vendors and users. This position is crucial for building next-generation infrastructure that serves hundreds of Large Language Model (LLM) based applications, directly contributing to the company’s advanced AI capabilities and platform offerings.

The TL;DR
• Role: Internship
• Type: Temporary (12 weeks)
• Location: US-based (remote option available, specific city not listed)
• Pay: $45 hourly
• Team: Applied Machine Learning Enterprise team
• Mission: Develop and operate a big model service platform that offers businesses Model-as-a-Service solutions.
• Tech Stack: PyTorch, TensorFlow, C++, Python, Go

What You’ll Actually Do
• Develop: Design and implement the core architecture for a next-generation big model as a service platform.
• Maintain: Support and enhance platform functionalities, specifically for offline training, finetuning, and online inference.
• Manage: Oversee the efficient management of model lifecycles and resource orchestration within the platform.
• Optimize: Strategically manage a large number of GPU resources to ensure efficient provision of computing power.
• Contribute: Support the Applied Machine Learning Enterprise team in combining system engineering and machine learning to deliver Model-as-a-Service solutions.

The Must-Haves
• Background: Currently pursuing a Bachelors or Masters in Computer Science or a related technical field; student level.
• Experience: Proficient in deep learning frameworks such as PyTorch or TensorFlow, with practical experience applying them to relevant business scenarios; demonstrated software development experience in at least one of C++, Python, or Go, combined with strong programming capabilities and good code design principles.
• Skills: Deep learning frameworks (PyTorch, TensorFlow), C++, Python, Go, software development, teamwork, communication, code design.
• Bonus: Preferred qualifications include practical experience with Natural Language Processing (NLP) and Large Language Model (LLM) technologies, including research or application of alignment techniques for LLMs; familiarity with ModelOps practices such as large model management and finetuning workflow management; and a strong academic background evidenced by contributions to top-tier conference papers like NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, or KDD.