Software Engineer Graduate (AI Compute)

About the Role

The Inference Infrastructure team is responsible for designing and operating platforms that power microservices, big data, distributed storage, machine learning training and inference, and edge computing. The team is focused on LLM inference infrastructure and is looking for engineers passionate about cloud-native systems, scheduling, and GPU acceleration.

Key Responsibilities

• Design and build large-scale, container-based cluster management and orchestration systems with extreme performance, scalability, and resilience.
• Architect next-generation cloud-native GPU and AI accelerator infrastructure to deliver cost-efficient and secure ML platforms.
• Collaborate across teams to deliver world-class inference solutions using vLLM, SGLang, TensorRT-LLM, and other LLM engines.
• Stay current with the latest advances in open source (Kubernetes, Ray, etc.), AI/ML and LLM infrastructure, and systems research; integrate best practices into production systems.
• Write high-quality, production-ready code that is maintainable, testable, and scalable.

Requirements & Tech Stack

Minimum Qualifications:

• Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Strong understanding of large model inference, distributed and parallel systems, and/or high-performance networking systems.
• Hands-on experience building cloud or ML infrastructure in areas such as resource management, scheduling, request routing, monitoring, or orchestration.
• Solid knowledge of container and orchestration technologies (Docker, Kubernetes).
• Proficiency in at least one major programming language (Go, Rust, Python, or C++).

Preferred Qualifications:

• Experience contributing to or operating large-scale cluster management systems (e.g., Kubernetes, Ray).
• Experience with workload scheduling, GPU orchestration, scaling, and isolation in production environments.
• Hands-on experience with GPU programming (CUDA) or inference engines (vLLM, SGLang, TensorRT-LLM).
• Familiarity with public cloud providers (AWS, Azure, GCP) and their ML platforms (SageMaker, Azure ML, Vertex AI).
• Strong knowledge of ML systems (Ray, DeepSpeed, PyTorch) and distributed training/inference platforms.
• Excellent communication skills and ability to collaborate across global, cross-functional teams.
• Passion for system efficiency, performance optimization, and open-source innovation.

About ByteDance

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. The company offers a suite of products including TikTok, Lemon8, CapCut, Pico, Toutiao, Douyin, and Xigua. ByteDance fosters a culture of curiosity, humility, and a desire to make an impact, with an "Always Day 1" mindset.