Software Engineer focused on building and maintaining large-scale, Kubernetes-native AI compute infrastructure for LLM inference, emphasizing performance, scalability, and cost-efficiency. The role involves architecting GPU-optimized systems and collaborating on inference solutions using various LLM engines.

Software Engineer focused on building and maintaining large-scale, Kubernetes-native LLM inference infrastructure (AIBrix) with a focus on performance, scalability, and cost-efficiency. The role involves architecting GPU-optimized systems, collaborating on inference solutions using various LLM engines, and contributing to open-source projects.

This role focuses on designing and developing DPU network software and exploring AI/ML infrastructure acceleration, specifically for distributed training and inference. It involves software-hardware co-design and performance optimization of systems related to AI computing.

ByteDance is seeking a Cloud Acceleration Engineer to focus on DPU and AI infrastructure. The role involves designing and developing high-performance DPU network software, collaborating on software-hardware co-design, and exploring AI/ML infrastructure acceleration for distributed training and inference. The position requires strong C/C++ and Linux systems development skills, with a background in areas like software-hardware co-design, distributed systems, networking, or AI/ML systems.

Senior Software Engineer to build AI-powered developer tools, focusing on retrieval infrastructure (RAG), a coding agent with multi-step generation and tool use, and evaluation frameworks for measuring effectiveness. Requires strong Python/TypeScript, systems-level language experience, and practical LLM integration.

Tech Lead for an Applied Machine Learning (AML) team focused on building and advancing distributed orchestration platforms for recommendation systems, ads ranking, and search ranking. The role involves leading a team of ML Engineers, setting technical strategy for resource efficiency, distributed training, and online inference systems, and optimizing large-scale distributed orchestration and scheduling strategies.

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.

Machine Learning Platform Engineer to develop and maintain a platform supporting deep learning models for code development, testing, training, model deployment, and other core business functions. The role supports recommendation, advertising, and search systems, focusing on distributed training of large-scale deep learning models.

Senior Software Engineer to build AI-powered developer tools that integrate AI/ML into the toolchain to accelerate software development, improve code quality, and simplify engineering workflows. Focus on intelligent assistants, static/dynamic analyzers, and smart automation features.

Software Engineer role focused on building and optimizing large-scale compute infrastructure (Kubernetes, Serverless) to support AI and LLM workloads, including training and inference. The role involves enhancing cluster management, developing intelligent scheduling systems leveraging AI models for resource optimization, and leading infrastructure for next-gen ML workloads.

Senior Software Engineer focused on building and optimizing large-scale compute infrastructure (Kubernetes, Serverless) for AI and LLM workloads, including scheduling, resource management, and inference. The role involves developing intelligent scheduling systems using AI models and contributing to open-source projects.

Senior Software Engineer focused on building and optimizing large-scale compute infrastructure (Kubernetes, Serverless) for AI and LLM workloads, including scheduling, resource management, and inference. The role involves enhancing performance, scalability, and cost-efficiency for training and inference, with a focus on heterogeneous resources (CPU, GPU) and open-sourcing key technologies.

Software Engineer role focused on building and optimizing large-scale compute infrastructure (Kubernetes, Serverless) for AI and LLM workloads, emphasizing resource efficiency, scheduling, and reliability. The role involves developing intelligent scheduling systems leveraging AI models and leading infrastructure for ML training/inference.

Machine Learning Engineer focused on optimizing and deploying AI algorithms on Qualcomm chips for XR devices, emphasizing low-power consumption and performance improvement. This role involves close collaboration with hardware vendors and contributing to the AI toolchain and technical ecosystem.

Machine Learning Engineer focused on NLP and Knowledge Graphs for TikTok E-commerce. Responsibilities include constructing massive product knowledge graphs to enhance feed ranking, recommendations, and ads, and collaborating with cross-functional teams on product strategies. Requires a Bachelor's degree, 3+ years of ML/NLP/CV experience, and proficiency in C++/Python/Go/Java.

Site Reliability Engineer for an Applied Machine Learning team focused on next-generation recommendation algorithms and platforms. The role involves ensuring high availability and creating automated systems for large-scale AI/recommendation systems.

Develops and optimizes high-speed network infrastructure and communication frameworks specifically for AI/LLM applications, focusing on performance, scalability, and reliability in large-scale data centers.