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

NWU; Seattle (WA); On-site; USD 49,000 - 69,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Wellbeing benefits

10 paid holidays per year

Housing allowance for interns

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Go

C++

Python

Data structures

Algorithms

Linux

Distributed systems

Concurrency

Problem solving

Collaboration

Education

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

Tools

Kubernetes

Container runtimes

Job description

Your Role

Here’s what you will be doing:

• Design and build foundational orchestration capabilities for machine learning platforms, including Kubernetes Operators, container runtimes, and lifecycle management for jobs, services, and stateful workloads.
• Develop multi-tenant resource and quota systems supporting priorities, preemption, fair sharing, elasticity, and cross-cluster scheduling to improve GPU utilization and cost efficiency.
• Build lifecycle orchestration for online model serving, including model and image distribution, deployment, upgrades, rollback, autoscaling, multi‑cluster operation, and disaster recovery.
• Create serving orchestration and traffic management capabilities for disaggregated serving clusters, including topology‑aware scheduling, KV Cache affinity, intelligent request routing, and QoS/SLA management.

About You

The company is looking for candidates who meet the following qualifications:

• Currently pursuing 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 a solid foundation in data structures, algorithms, and software engineering principles.
• Familiarity with Linux and foundational understanding of operating systems, computer networks, concurrent programming, and distributed systems.
• Strong hands‑on and exploratory abilities, with willingness to investigate systems through source code, metrics, logs, profiling, and experiments.
• A systematic and quantitative approach to problem solving, including defining measurements, testing hypotheses, and validating system improvements.
• Demonstrated ownership and collaboration through coursework, research, internships, open‑source contributions, or other engineering projects.

Preferred qualifications include experience with Kubernetes, container runtimes, resource scheduling, quota management, multi‑tenant systems, FinOps, contributions to open‑source infrastructure projects, familiarity with model serving systems, online services, traffic management, autoscaling, performance optimization, distributed systems, GPU/NPU programming, heterogeneous resource scheduling, model distribution, or inference performance analysis.

Compensation & Benefits

• Hourly rate of $42.75.
• Day one access to health insurance, life insurance, wellbeing benefits, and more.
• 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 hours if hired in second half).
• Housing allowance eligibility for interns not working 100% remotely.