AI Compute Systems Engineer (PhD Grad) 2027 Start

Pangle; San Jose (CA); Hybrid; USD 162,000 - 317,000; Full time

Job summary

ByteDance’s Inference Infrastructure team is hiring a Software Engineer Graduate (AI Compute) in San Jose to join the Kubernetes-native control plane for large-scale LLM inference. You will work on cloud-native GPU and AI accelerator infrastructure, contributing to open-source and production-grade systems.

As a PhD candidate or recent graduate, you will collaborate across teams to push performance, scalability, and cost-efficiency in AI workloads, with opportunities to influence next-gen

Qualifications

• PhD in Software Development, Computer Science, Computer Engineering, or related technical discipline.
• Strong understanding of large model inference, distributed and parallel systems, and/or high-performance networking.
• Hands-on experience building cloud or ML infrastructure including resource management, scheduling, monitoring, or orchestration.
• Solid knowledge of container and 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 ML platforms.
• Collaborate across teams to deliver inference solutions using various LLM engines.
• Stay current with open source, AI/ML and LLM infrastructure, and integrate best practices into production systems.
• Write high-quality, production-ready code that is maintainable and testable.

Skills

Large model inference

Distributed systems

High-performance networking

Container orchestration

Go

Rust

Python

C++

Education

PhD in Software Development / CS / CE

Tools

Docker

Kubernetes

Job description

ByteDance’s Inference Infrastructure team is hiring a Software Engineer Graduate (AI Compute) in San Jose to join the Kubernetes-native control plane for large-scale LLM inference. You will work on cloud-native GPU and AI accelerator infrastructure, contributing to open-source and production-grade systems.

As a PhD candidate or recent graduate, you will collaborate across teams to push performance, scalability, and cost-efficiency in AI workloads, with opportunities to influence next-gen