Linux Engineer

Kerry Search Partners

Detroit (MI)

On-site

USD 160,000 - 170,000

Full time

14 days+

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Benefits offered by this job

Medical insurance

Pension plan

Paid paternity leave

Tuition assistance

Disability insurance

Child care support

Vision insurance

Paid maternity leave

Student loan assistance

401(k)

Job summary

A leading semiconductor firm based in Detroit is looking for a Mid-Senior level professional to build a foundational Generative AI platform. This full-time opportunity involves operating both on-premises GPU infrastructure and cloud environments. Responsibilities include designing Kubernetes-based AI systems and ensuring high availability and scalability. Candidates should have strong experience in Linux systems, Kubernetes, and GPU infrastructure management, making this a key role to drive technological innovation.

Qualifications

Deep experience deploying, operating, and troubleshooting Kubernetes systems.
Hands-on experience building and operating AI/ML platforms.
Strong knowledge of configuring GPU infrastructure for AI workloads.

Responsibilities

Build and operate a GenAI platform for internal products.
Design Kubernetes-based AI infrastructure on on-prem GPU clusters.
Configure and manage LLMs for enterprise applications.

Skills

Linux systems background

Kubernetes expertise

AI/ML platform experience

GPU infrastructure management

LLMs and vector databases knowledge

HPC environment experience

Hybrid environment operations

Tools

Kubernetes

GPU infrastructure

Linux

Job description

Kerry Search Partners provided pay range

This range is provided by Kerry Search Partners. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$160,000.00/yr - $170,000.00/yr

Job Overview

We are a global leader in the semiconductor manufacturing ecosystem, driving the technology behind virtually every electronic device in the world. Our innovations power the production of laptops, smartphones, VR devices, smart cars, and more. At the forefront of technological advancement, we invest heavily in research and development, fostering an environment where innovation thrives. Our teams of engineers, data scientists, and problem-solvers tackle the toughest challenges, ensuring no two days are the same.

Group/Division

The Information Technology team plays a critical role in supporting the organization’s global operations. IT connects people, processes, and technology to enhance business growth and employee productivity. By focusing on user empowerment and process excellence, IT helps unlock the full potential of advanced technology to drive operational success.

The Opportunity

We are building a core Generative AI platform to enable internal engineering, IT, and business teams to rapidly prototype and deploy GenAI applications. This role is not application development—it is about designing, building, and operating the foundational AI platform that others will consume.

The platform will support both on‑premises GPU infrastructure and cloud environments, with Kubernetes at its core. You’ll work on everything from GPU provisioning and LLM deployment to vector databases, security, and reliability—owning the platform end to end.

What You’ll Be Working On

Build and operate a GenAI platform that supports internal products such as AI assistants and engineering tooling
Design and maintain Kubernetes‑based AI infrastructure running on on‑prem GPU clusters and cloud environments
Configure and manage LLMs (e.g., open‑source models such as LLaMA variants) for enterprise use
Deploy and operate vector databases to support retrieval‑augmented generation (RAG) workflows
Ensure high availability, scalability, and efficient GPU utilization across expensive compute environments
Partner closely with ML engineers and application teams who will build on top of the platform you create
Implement secure, compliant, and observable infrastructure suitable for enterprise adoption
Leverage Linux and open‑source tooling to optimize performance in high‑performance computing (HPC) environments

Key Technical Requirements

Strong Linux systems background (on‑prem experience is essential)
Deep experience with Kubernetes as a core platform (deploying, operating, troubleshooting)
Hands‑on experience building or operating AI/ML platforms (not just consuming them)
Experience configuring and managing GPU infrastructure for AI/ML workloads
Familiarity with LLMs, GenAI infrastructure, and vector databases
Exposure to HPC environments and high‑throughput workloads
Experience operating platforms across on‑prem, cloud, or hybrid environments