ML Platform Engineer Intern - Orchestration & Serving

NWU; Seattle (WA); Presencial; USD 49.000 - 69.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Life insurance

Wellbeing benefits

10 paid holidays per year

Housing allowance for interns

Descripción de la vacante

NWU in Seattle is seeking students to help design and build foundational orchestration for ML platforms. You will work on Kubernetes Operators, resource quotas for multi-tenant clusters, and lifecycle tooling for online model serving and deployment workflows.

Ideal candidates are pursuing CS/SE/AI degrees, proficient in Go/C++/Python, and comfortable with Linux, distributed systems, and exploratory research.

Formación

• Enrolled in a Bachelor's or Master's program in CS/SE/AI.
• Proficient in Go, C++, or Python with solid CS fundamentals.
• Familiar with Linux and basic OS, networks, and distributed systems concepts.
• Strong hands-on, exploratory mindset with ability to analyze systems via code, logs, and metrics.
• Proven ownership and collaboration through coursework, internships, or projects.

Responsabilidades

• Design and build orchestration capabilities for ML platforms, incl. Kubernetes Operators and lifecycle management for jobs and services.
• Develop multi-tenant resource and quota systems to improve GPU utilization and cost efficiency.
• Build lifecycle orchestration for online model serving, including deployment, upgrades, and autoscaling.
• Create serving orchestration and traffic management for disaggregated clusters with topology-aware scheduling.

Conocimientos

Go

C++

Python

Data structures

Algorithms

Linux

Distributed systems

Concurrency

Problem solving

Collaboration

Educación

Bachelor's or Master's in CS/SE/AI or related

Herramientas

Kubernetes

Container runtimes

Descripción del empleo

NWU in Seattle is seeking students to help design and build foundational orchestration for ML platforms. You will work on Kubernetes Operators, resource quotas for multi-tenant clusters, and lifecycle tooling for online model serving and deployment workflows.

Ideal candidates are pursuing CS/SE/AI degrees, proficient in Go/C++/Python, and comfortable with Linux, distributed systems, and exploratory research.