Graduate Software Engineer: ML Infra & Orchestration

ByteDance; Seattle (WA); On-site; USD 110,000 - 150,000; Full time

Job summary

ByteDance is seeking graduates to join the Data-AML-Engine Orchestration team in Seattle. You will help build large-scale ML infrastructure that powers TikTok and other products, focusing on orchestration, scheduling, and resource management for production workloads.

You will design foundational capabilities, drive improvements in GPU utilization, latency, and reliability, and collaborate across teams to deliver scalable machine learning systems with opportunities for growth.

Qualifications

• Bachelor's or Master's in Computer Science, Software Engineering, AI, or related technical field.
• Proficiency in Go, C++, or Python with solid data structures and algorithms knowledge.
• Familiarity with Linux, OS concepts, networks, and distributed systems.
• Hands-on, exploratory mindset and ability to measure and validate improvements.
• Demonstrated ownership and collaboration through coursework or projects.

Responsibilities

• Design and build foundational orchestration capabilities for ML platforms, including Kubernetes Operators and lifecycle management for jobs and services.
• Create multi-tenant resource and quota systems to improve GPU utilization and cost efficiency.
• Develop lifecycle orchestration for online model serving with deployment, upgrades, and autoscaling.
• Implement serving orchestration and traffic management for disaggregated clusters with QoS/SLA control.

Skills

Go

C++

Python

Linux

Distributed systems

Data structures

Algorithms

Education

Bachelor's or Master's in Computer Science/Software Engineering/AI

Tools

Kubernetes

Volcano

Koordinator

OpenKruise

Job description

ByteDance is seeking graduates to join the Data-AML-Engine Orchestration team in Seattle. You will help build large-scale ML infrastructure that powers TikTok and other products, focusing on orchestration, scheduling, and resource management for production workloads.

You will design foundational capabilities, drive improvements in GPU utilization, latency, and reliability, and collaborate across teams to deliver scalable machine learning systems with opportunities for growth.