ByteDance currently has 112 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 39% of the total, followed by agents at 27%. Engineering is the most frequent function, with research also being a significant area. The company is hiring for these positions primarily in the United States. Frequent tech tags include model_serving, inference_infra, and multimodal. In the last 30 days, ByteDance added 14 new AI roles, representing a 27% increase compared to the previous 30-day period.
Currently tracking 109 active AI roles, down 43% versus the prior 4 weeks. Primary focus: Serve · Engineering.
ByteDance currently has 115 active AI-related roles in our index. The most common open titles are: Cloud Acceleration Engineer – DPU & AI Infra (2), LLM AIOps Development Engineer - Data Center Networking (2), Multimodal Model Training and Inference Optimization Engineer (2), Research Engineer - LLM Training Infrastructure - Seed Infra (2), Research Engineer - LLM/VLM Inference Optimization (Seed Infra) (2). Most positions are in Engineering and Research.
ByteDance's active AI hiring is concentrated in: serving infrastructure (38%), agents (25%), post-training (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
ByteDance is hiring AI talent in: United States (115 roles).
Job postings at ByteDance most frequently mention: Machine Learning, Production ML Systems, Algorithms & Data Structures, GPU Computing, Optimization Methods.
In the past 30 days, ByteDance has posted 2 new AI-related roles. That is a -78% change versus the prior 30 days (9 → 2).
| Title | Stage | AI score |
|---|---|---|
| Senior Research Scientist (Multimodal Large Language Model) - PICO Research Scientist role focused on developing multimodal large language models (MLLM) with tool-use capabilities for Mixed Reality (MR) environments. This involves optimizing model architectures, enabling tool utilization for complex tasks, and addressing challenges in long-horizon, multi-turn interactions. The role also includes applying and deploying innovative technologies in PICO's MR products and collaborating with cross-functional teams. | AgentPost-train | 9 |
| Research Scientist, Operations Research (Infrastructure Lab) Research Scientist role focusing on operations research for AI-native data infrastructure. The role involves designing and optimizing vector indexing algorithms for vector databases, and exploring the integration of LLM, RL, and Agent technologies into operations research optimization pipelines. This includes developing AI for infrastructure optimization and LLM-based tooling like NL2SQL. |
| AgentData |
| 7 |
| Senior Research Scientist, Operations Research (Infrastructure Lab) Research Scientist role focused on designing and optimizing state-of-the-art vector indexing algorithms for next-generation vector database infrastructure, and exploring AI for Operations Research by integrating LLM, RL, and Agent technologies into optimization pipelines. | AgentData | 7 |
| Research Scientist, Operations Research (Infrastructure Lab) Research Scientist role focused on designing and optimizing state-of-the-art vector indexing algorithms and integrating AI (LLM, RL, Agent) into operations research optimization pipelines for AI data centers and cloud resource scheduling. The role involves building next-generation AI-native data infrastructure, including vector databases and intelligent algorithms for infrastructure optimization. | AgentData | 7 |
| Research Scientist, Infrastructure System Lab Research Scientist role focused on designing and optimizing state-of-the-art vector indexing algorithms for large-scale similarity search and retrieval, powering next-generation vector databases. The work involves research into ANN search, optimization for performance, and collaboration with engineering for productionization, with a strong emphasis on academic publications and staying current with AI x systems research. | AgentData | 7 |
| Research Scientist, Infrastructure System Lab Research Scientist focused on designing and optimizing state-of-the-art vector indexing algorithms for large-scale similarity search, filtered search, and hybrid retrieval use cases. The role involves developing new algorithms, optimizing for performance, and collaborating with engineering teams for productionization, with a strong emphasis on academic publications and staying current with AI x systems research. | AgentData | 7 |