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Internship Ai Infrastructure Engineer Jobs (NOW HIRING)

vCluster Labs

AI Infrastructure Engineer

New York, NY · Remote

$150K - $200K/yr

As an AI Infrastructure Engineer, your role will include: * Lead Technical Deployments: Drive end-to-end technical deployments for GPU neocloud and AI Factory customers, from initial bare metal ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

AMAX

AI Infrastructure Engineer

Fremont, CA

$117K - $154K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

Spellbrush

AI Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Spellbrush, the world's leading generative AI studio behind niji・journey , is looking for an AI Infrastructure Engineer to join us in building out end-to-end ML infrastructure to run our models on ...

Spellbrush

AI Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Spellbrush, the world's leading generative AI studio behind niji・journey , is looking for an AI Infrastructure Engineer to join us in building out end-to-end ML infrastructure to run our models on ...

NIO

AI Infrastructure Engineer

San Jose, CA · On-site

$126K - $165K/yr

About the Position We are looking for a senior AI Inference Infrastructure Software Engineer with strong hands-on experience building, optimizing, and deploying high-performance, scalable inference ...

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How much do internship ai infrastructure engineer jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for internship ai infrastructure engineer in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is the difference between Internship Ai Infrastructure Engineer vs Data Engineer?

AspectInternship Ai Infrastructure EngineerData Engineer
Required CredentialsEnrolled in or recent graduate of Computer Science, Engineering, or related fields; some knowledge of AI and infrastructure toolsBachelor's or higher in Computer Science, Data Science, or related; experience with databases and data pipelines
Work EnvironmentInternship setting, collaborative teams, learning-focusedFull-time, technical teams managing data systems and pipelines
Employer & Industry UsageTech companies, AI startups, research labsTech firms, finance, healthcare, and other data-driven industries

The Internship Ai Infrastructure Engineer role focuses on supporting AI infrastructure projects during an internship, emphasizing learning and assisting with AI systems setup. In contrast, Data Engineers build and maintain data pipelines and infrastructure for data analysis. While both roles require knowledge of technical tools, the internship role is more entry-level and learning-oriented, whereas Data Engineers are more experienced and responsible for ongoing data management.

What does an Internship AI Infrastructure Engineer do?

An Internship AI Infrastructure Engineer assists in designing, developing, and maintaining the foundational systems that support artificial intelligence (AI) applications. They work with cloud platforms, data pipelines, and scalable computing resources to ensure that AI models can be trained and deployed efficiently. Interns may help automate workflows, optimize performance, and collaborate with data scientists and software engineers. The role provides hands-on experience with the tools and frameworks commonly used in AI engineering environments.

What are the key skills and qualifications needed to thrive as an Internship AI Infrastructure Engineer, and why are they important?

To thrive as an Internship AI Infrastructure Engineer, you need a solid understanding of computer science fundamentals, programming (especially in Python or C++), and basic knowledge of machine learning frameworks, often supported by ongoing studies in a relevant field. Familiarity with cloud platforms (like AWS, GCP, or Azure), version control systems (such as Git), and containerization tools (Docker, Kubernetes) is typically expected. Strong problem-solving abilities, curiosity, teamwork, and effective communication help interns stand out and integrate quickly into engineering teams. These skills are crucial for supporting scalable AI solutions, collaborating on complex projects, and contributing meaningfully in a fast-evolving technical environment.

What types of projects and responsibilities can an AI Infrastructure Engineer intern expect to work on?

As an AI Infrastructure Engineer intern, you can expect to be involved in projects that support the development, deployment, and scaling of AI models. Typical responsibilities may include optimizing data pipelines, maintaining and improving cloud or on-premise computing resources, and collaborating closely with data scientists to ensure efficient model training and inference. Interns often get hands-on experience with tools such as Docker, Kubernetes, and various cloud platforms, and work in cross-functional teams to troubleshoot and enhance AI workflows. This role provides a solid foundation in both software engineering and AI operations, preparing you for advanced positions in the field.
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Internship Ai Infrastructure Engineer jobs near you
Infographic showing various Internship Ai Infrastructure Engineer job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.
AI Infrastructure Engineer

AI Infrastructure Engineer

Advanced Micro Devices, Inc

San Jose, CA • On-site

$178K/yr

Full-time

Posted 2 days ago

Advanced Micro Devices rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

19th of 144 rated electronics manufacturers

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE PERSON:
We are seeking a DevOps / Platform Engineer to join our team building and operating large-scale GPU compute infrastructure that powers AI and ML workloads. The ideal candidate should be passionate about software engineering and possess leadership skills to independently deliver on multi-quarter projects. They should be able to caommunicate effectively and work optimally with their peers within our larger organization. Finally, you aren't afraid of a team in more of a startup mode at a larger company and willing to jump in to help in areas adjacent to your main project as needed.
Key Responsibilities
  • Build and extend platform capabilities to enable new classes of workloads (e.g., interactive development pods, CI pipelines, inference services, benchmarking jobs).
  • Design and operate scalable orchestration systems using Kubernetes across both on-prem and multi-cloud environments.
  • Develop platform features such as secret management, configuration management, and deployment automation for customers.
  • Partner with development teams to extend the GPU developer platform with features, APIs, templates, and self-service workflows that streamline job orchestration and environment management.
  • Manage service lifecycle within Kubernetes using Helm and GitOps workflows (e.g., ArgoCD or Flux).
  • Apply expertise in storage and networking to design and integrate CSI drivers, persistent volumes, and network policies that enable high-performance GPU workloads.

Required Qualifications
  • Experience in DevOps, Platform, or Infrastructure Engineering.
  • Deep hands-on experience with Kubernetes and container orchestration at scale.
  • Proven ability to design and deliver platform features that serve internal customers or developer teams
  • Experience building developer-facing platforms or internal developer portals (e.g.custom workflow tooling).

Nice to Have
  • Hands-on experience in storage or network engineering within Kubernetes environments (e.g., CSI drivers, dynamic provisioning, CNI plugins, or network policy).
  • Experience with Infrastructure as Code tools like Terraform.
  • Background in HPC, Slurm, or GPU-based compute systems for ML/AI workloads.
  • Practical experience with monitoring and observability tools (Prometheus, Grafana, Loki, etc.).
  • Understanding of machine learning frameworks (PyTorch, vLLM, SGLang, etc.).

#LI-G11
#LI-HYBRID
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
This posting is for an existing vacancy.

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