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Internship Ai Infrastructure Engineer Jobs in California

Palona AI

AI Infrastructure Engineer

Los Altos, CA · On-site

$127K - $167K/yr

We are looking for an Infrastructure Engineer who combines cloud and reliability depth with strong software engineering judgment. You will build and operate the platform beneath Palona's AI products ...

Palona AI

AI Infrastructure Engineer

Los Altos, CA · On-site

$150 - $230/hr

We are looking for an Infrastructure Engineer who combines cloud and reliability depth with strong software engineering judgment. You will build and operate the platform beneath Palona's AI products ...

Palona AI

AI Infrastructure Engineer

Los Altos, CA · On-site

$127K - $167K/yr

We are looking for an Infrastructure Engineer who combines cloud and reliability depth with strong software engineering judgment. You will build and operate the platform beneath Palona's AI products ...

MeshyAI

AI Infrastructure Engineer

Sunnyvale, CA · On-site

$125K - $164K/yr

The AI Infrastructure Engineer role involves ensuring the reliability and scalability of the AI model serving stack, while developing core engineering infrastructure to connect models to product ...

Socket.dev

AI Infrastructure Engineer

Los Altos, CA · On-site

$110 - $170/hr

We are looking for an Infrastructure Engineer who combines cloud and reliability depth with strong software engineering judgment. You will build and operate the platform beneath Palona's AI products ...

Spellbrush

AI Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Spellbrush is the world's leading generative AI studio behind niji・journey, and they are seeking an AI Infrastructure Engineer to build out end-to-end ML infrastructure. The role involves designing ...

Gatik AI

Senior AI Infrastructure Engineer

Santa Clara, CA · On-site

$127K - $173K/yr

About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on ...

Gatik AI

Senior AI Infrastructure Engineer

Santa Clara, CA · On-site

$127K - $173K/yr

About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on ...

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 · On-site

$140 - $190/hr

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

Visa Hunt

AI Infrastructure Engineer

San Francisco, CA · On-site

$180 - $240/hr

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 ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$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)

NIO USA, INC

AI Infrastructure Engineer

San Jose, CA

$192K - $249K/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 ...

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 ...

Intel

AI Infrastructure Engineer

Santa Clara, CA · On-site

$170K - $315K/yr

We are looking for a performance-obsessed AI Infrastructure Engineer to push LLM inference to its absolute limits on Intel's next-generation GPU architectures. In this role, you will dive deep into ...

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All JobsAi Infrastructure Engineer JobsInternship Ai Infrastructure Engineer JobsInternship Ai Infrastructure Engineer Jobs in California

Internship Ai Infrastructure Engineer information

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 types of projects and responsibilities can an internship AI infrastructure engineer 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.

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 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 are the most commonly searched types of Ai Infrastructure Engineer jobs in California?

The most popular types of Ai Infrastructure Engineer jobs in California are:

What are popular job titles related to Internship Ai Infrastructure Engineer jobs in California?

For Internship Ai Infrastructure Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Ai Infrastructure Engineer jobs in California look for?

The top searched job categories for Internship Ai Infrastructure Engineer jobs in California are:

What cities in California are hiring for Internship Ai Infrastructure Engineer jobs?

Cities in California with the most Internship Ai Infrastructure Engineer job openings:

Internship Ai Infrastructure Engineer jobs near you
Infographic showing various Internship Ai Infrastructure Engineer job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

AI Infrastructure Engineer

Palona AI

Los Altos, CA • On-site

$127K - $167K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 12 days ago

Job description

Palona's AI agents operate continuously in production, handle real-time guest interactions, integrate with restaurant systems, and face sharp traffic peaks. Infrastructure is therefore part of the product: latency, reliability, deployment safety, observability, security, and cost directly shape the guest and operator experience.

We are looking for an Infrastructure Engineer who combines cloud and reliability depth with strong software engineering judgment. You will build and operate the platform beneath Palona's AI products, improve how engineers ship, and turn production signals into durable system improvements. This is not a ticket-driven IT or operations role. You will write production code, design systems, automate repetitive work, and own outcomes across the full service lifecycle.

Our current environment includes Python services, Docker, AWS and selected Azure services, ECS and Lambda workloads, API Gateway, load balancers, relational data systems, OpenTofu/Terraform, Datadog, and CI/CD automation. We value the ability to learn and make sound tradeoffs more than exact tool-for-tool matching.

What you will own:
  • Design, build, and evolve secure, scalable cloud infrastructure for real-time AI services and customer-facing applications.
  • Improve service reliability through clear SLOs, actionable observability, capacity planning, failure testing, and pragmatic incident prevention.
  • Build deployment and release systems that make production changes fast, repeatable, auditable, and safe.
  • Own infrastructure as code, environment consistency, and reusable platform patterns across development, staging, and production.
  • Partner with product and AI engineers on architecture, performance, data flows, and operational readiness for new capabilities.
  • Diagnose complex distributed-system failures across application, network, database, model-provider, and third-party integration boundaries.
  • Reduce infrastructure and model-serving cost without compromising customer experience or engineering velocity.
  • Strengthen secrets management, access controls, backup and recovery, vulnerability management, and other practical security foundations.
  • Build internal tooling and paved paths that let engineers ship and operate services with less manual work.
  • Participate in incident response and turn incidents into better systems, automation, documentation, and engineering judgment.

Requirements

  • 3+ years industrial experience in relevant technical domain.
  • Strong software engineering fundamentals and experience building or operating production distributed systems.
  • Hands-on experience with a major cloud platform; AWS experience is especially relevant.
  • Experience with containers, infrastructure as code, CI/CD, monitoring, alerting, and production debugging.
  • Ability to write reliable automation and services in Python or another modern programming language.
  • Sound judgment around availability, latency, scalability, security, and cost tradeoffs.
  • A track record of taking ambiguous operational problems from diagnosis through durable resolution.
  • Clear communication during architecture reviews, launches, and incidents.
  • AI-native working habits and curiosity about the operational behavior of LLM- and agent-powered systems.

Benefits

  • Competitive Salary and Stock Option Plan.
  • Medical, dental, vision, retirement, leave, and disability benefits as applicable.
  • Family Leave
  • Short Term & Long Term Disability
  • Paid time off and company holidays.
  • Learning and development support.

Apply