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.
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).
Currently tracking 109 active AI roles, down 43% versus the prior 4 weeks. Primary focus: Serve · Engineering.
| Title | Stage | AI score |
|---|---|---|
| Applied Machine Learning Engineer, Smart Devices (PICO-Lab) - San Jose Applied Machine Learning Engineer role focused on developing AI applications for next-generation XR smart devices (MR headsets, AR glasses, wearables). The role involves leading AI software prototyping, user studies, creating and deploying multimodal AI features, developing and maintaining ML models (leveraging open models and training new ones), designing evaluation frameworks, and staying updated on ML techniques. Requires a Master's or PhD in CS with 5+ years of ML infrastructure experience, including model deployment, evaluation, optimization, and data processing. Expertise in NLP, LLM, or Computer Vision is preferred. | ShipPost-train | 8 |
| Machine Learning Engineer - Data Recommendation (CapCut) |
| Ship |
| 7 |
| Recommender System Engineer, AI-Driven (PICO-Lab) - San Jose Recommender System Engineer focused on building and productionizing recommendation models, designing low-latency serving pipelines, and running experiments for XR products. | Ship | 7 |
| Machine Learning Engineer (User Growth & Intelligent Marketing) - Global e-Commerce Machine Learning Engineer focused on optimizing user growth and intelligent marketing algorithms for TikTok's e-commerce platform. This role involves developing and implementing solutions for personalized recommendations, user value modeling, uplift modeling, and marketing efficiency to drive e-commerce GMV growth. | Ship | 7 |
| Machine Learning Engineer, Search - Local Services Team Machine Learning Engineer for ByteDance's Local Services team, focusing on enhancing user discovery and ecosystem growth for hospitality, dining, and leisure experiences. The role involves leveraging large-scale ML for search and recommendation systems, aiming to improve personalized relevance, CTR/CVR prediction, and conversion efficiency for billions of users. Responsibilities include designing and implementing full-stack search algorithms, query analysis, ranking, and personalized behavior modeling. | Ship | 7 |
| Senior Machine Learning Engineer - Data Recommendation (CapCut) Senior Machine Learning Engineer focused on recommendation algorithms for video creation tools like CapCut and Hypic, aiming to optimize content distribution and drive user growth. | Ship | 7 |