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

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

Benefits offered by this job

Health insurance

Wellbeing benefits

10 paid holidays per year

Housing allowance eligibility

Job summary

Thinklance LLP is seeking an engineering intern in Seattle to help design and build orchestration for ML platforms, including Kubernetes operators and lifecycle management for jobs and workloads.

You will work on multi-tenant resource systems, multi-cluster scheduling, and model serving orchestration with autoscaling and disaster recovery considerations. Ideal candidates are pursuing CS/SE/AI degrees with strong coding skills in Go, C++, or Python and a penchant for systems work.

Qualifications

• Pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, AI or related field.
• Proficiency in Go, C++, or Python with solid CS fundamentals.
• Familiarity with Linux and distributed systems basics.
• Strong problem-solving and collaborative mindset.

Responsibilities

• Design and build orchestration for ML platforms, including operators and lifecycle management.
• Develop multi-tenant resource and quota systems to improve GPU utilization and cost efficiency.
• Build serving orchestration for online models, including deployment, upgrades, and autoscaling.
• Create topology-aware scheduling, traffic management, and QoS/SLA for disaggregated serving clusters.

Skills

Go

C++

Python

Education

Bachelor’s or Master’s degree in CS/SE/AI or related field

Tools

Kubernetes

Docker

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.