ByteDance

Product Manager for an AI coding product, focusing on defining model behavior, integration into developer pipelines, and identifying high-value developer scenarios. Responsibilities include tracking research, defining evaluation standards, and working with cross-functional teams to drive model improvements.

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.

Research Scientist role focused on building and scaling machine learning models for recommendation systems, including end-to-end generative systems and reinforcement learning for personalization. The role involves researching and applying multi-modal techniques, optimizing model architectures for large-scale training and inference, and collaborating with product and engineering teams for deployment. Requires expertise in deep learning, LLMs, multi-modal learning, and production ML pipelines, with a strong publication record.

Recommender System Engineer focused on building and productionizing recommendation models, designing low-latency serving pipelines, and running experiments for XR products.

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.

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.