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

What you'll do

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

What they ask for

• Completing or recently completed a Bachelor's or Master's degree 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.
• Demonstrated ownership and collaboration through coursework, research, internships, open-source contributions, or other engineering projects.

Nice to have

• Experience with Kubernetes, container runtimes, resource scheduling, quota management, multi-tenant systems, or FinOps.
• Experience with model-serving systems such as vLLM, SGLang, Triton, KServe, or Ray Serve, or related serving and inference concepts.

Tools

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

AI focus

Build machine-learning orchestration and online model-serving infrastructure, including scheduling, resource management, deployment, and serving traffic management.