ByteDance

Responsibilities

About the Team:

The Applied Machine Learning Enterprise team combines system engineering and machine learning to develop and operate the 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 researchers specializing in Large Language Models (LLM) to join our dynamic team.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with 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 for a maximum of TWO positions and will be considered for jobs in the order you applied for. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities:

In this role, you will be at the forefront of cutting-edge research and development of advanced techniques for MaaS solutions including model post-training: fine-tuning (SFT), reinforcement learning (RL), reasoning, evaluation, test-time techniques, prompt optimization, multi-modality, and also LLM application/agent development. Your primary responsibility will be to:

• Lead the investigation, exploration, and creation of next-generation, high-capacity LLM platforms and innovative products, while keeping close track with the latest AI technologies.
• Work closely with cross-functional teams to plan and implement projects harnessing LLMs for diverse purposes and vertical domains.
• Maintain a deep passion for contributing to the success of large models is essential in this innovative and fast-paced team environment.
• Design and develop AI agents for a wide range of AI native applications, including multi-modality(image/video/audio). Continuously improve the agent's ability of understanding, reasoning, tool selection, taking actions at blazing fast speed.

Qualifications

Minimum Qualifications:

• BS/MS in Computer Science, Artificial Intelligence, or a related field.
• Have prior experience working with training or inference of large language models (PyTorch or Tensorflow).
• Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, finetuning, alignment, RL, agent, etc.) and possess practical expertise in effectively implementing these advanced systems.
• Proficiency in programming languages such as Python or C++ and a track record of working with deep learning frameworks or agent frameworks.

Preferred Qualifications:

• Excellent problem-solving skills and a creative mindset to address complex AI challenges. Demonstrated ability to drive research projects from idea to implementation, producing tangible outcomes.
• Published research papers or contributions to the LLM community, top-tier conference (NeurIPS, ICML, ICLR, ACL, CVPR, ENMLP) publications would be a significant plus.
• Experience with building LLM Applications, have a deep understanding of Agentic frameworks, RAG, Test-time scaling, Reasoning, Evaluation, Multi-modality, etc.
• Experience with deploying AI applications into production environments, prompt optimizing, testing and evaluation of AI systems, LLM application & agent development is desirable.
• Experience or publications in multi-modal is a plus, including image/video/audio understanding, text-to-image, text-to-video, etc.