Graduate Software Engineer, AI Compute & Cloud Systems

ByteDance; Seattle (WA); On-site; USD 154,000 - 301,000; Full time

Job summary

ByteDance seeks a Software Engineer Graduate (AI Compute) in Seattle for 2027 start. You will work on large-scale, container-based cluster management and GPU-accelerated AI inference within the Inference Infrastructure team, part of Core Compute Infrastructure.

The role emphasizes cloud-native systems, scheduling, and open-source collaboration. The ideal candidate is completing a PhD in a related field with strong experience in distributed systems, container orchestration, and GPU/ML tooling.

Qualifications

• PhD in software development, CS, or related technical discipline.
• Strong understanding of large model inference, distributed/parallel systems, or high-performance networking.
• Hands-on experience building cloud or ML infrastructure (resource management, scheduling, monitoring, orchestration).
• Solid knowledge of container/orchestration technologies (Docker, Kubernetes).
• Proficiency in Go, Rust, Python, or C++.

Responsibilities

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

Skills

Large model inference

Distributed systems

High-performance networking

Docker

Kubernetes

Go

Rust

Python

C++

Education

PhD in Software Development/Computer Science/Computer Engineering

Tools

Docker

Kubernetes

Job description

ByteDance seeks a Software Engineer Graduate (AI Compute) in Seattle for 2027 start. You will work on large-scale, container-based cluster management and GPU-accelerated AI inference within the Inference Infrastructure team, part of Core Compute Infrastructure.

The role emphasizes cloud-native systems, scheduling, and open-source collaboration. The ideal candidate is completing a PhD in a related field with strong experience in distributed systems, container orchestration, and GPU/ML tooling.