Machine Learning Engineer Graduate (AML-Engine-Orchestration) - 2027 Start (PhD)

What you'll do

• Design orchestration capabilities for jobs and services, including Kubernetes Operators, container runtimes, and lifecycle management.
• Build multi-tenant resource and quota systems, scheduling, and resource-pooling capabilities to improve GPU utilization and cost efficiency.
• Develop model-serving lifecycle orchestration, traffic management, autoscaling, and multi-cluster reliability capabilities.

What they ask for

• Completing or recently completed a PhD in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field.
• Proficiency in at least one of Go, C++, or Python, with foundations in data structures, algorithms, and software engineering.
• Familiarity with Linux and foundational knowledge of operating systems, computer networks, concurrent programming, and distributed systems.
• Hands-on systems investigation and quantitative problem-solving abilities; demonstrated ownership and collaboration through projects or similar work.

Nice to have

• Experience with Kubernetes, container runtimes, resource scheduling, quota management, multi-tenant systems, or FinOps; open-source infrastructure contributions.
• Experience with model-serving systems or concepts, online services, traffic management, performance optimization, distributed systems, GPU/NPU programming, or inference analysis.

Tools

Go, C++, Python, Linux, Kubernetes, Volcano, Koordinator, OpenKruise

AI focus

Build and operate orchestration and resource-management infrastructure for machine learning workloads and online model serving, including model deployment, scheduling, routing, autoscaling, and inference performance.