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Internship Ai Infrastructure Engineer Jobs in Utah

Webhosting

Senior Infrastructure Engineer

Lehi, UT · On-site

$120 - $160/hr

Our AI-powered DigiCert ONE platform unifies PKI, DNS, and certificate lifecycle management, to ... Infrastructure Engineer to design, build, and maintain the enterprise infrastructure that runs ...

New

Doist

Senior Infrastructure Engineer

Lehi, UT · On-site

$120 - $170/hr

Our AI-powered DigiCert ONE platform unifies PKI, DNS, and certificate lifecycle management, to ... What you will have * 5+ years of hands‑on infrastructure engineering (hypervisors, storage ...

New

WorkBay

Data & Infrastructure Engineer

Draper, UT · On-site

$107K - $128K/yr

Support and extend our AI infrastructure, prompt configurations, evaluation suites, and cost ... engineering, platform engineering, or a related field * Strong proficiency in Python and SQL

Deloitte

AI Datacenter Associate VP

Salt Lake City, UT · Hybrid

AI Datacenter & Infrastructure Associate VP Join our AI & Engineering team and help transform technology platforms, drive innovation, and make a significant impact on our clients' success. You'll ...

Atonom

AI Revenue Engineer

Provo, UT · On-site

Join us as we build the infrastructure for the next generation of work. Role This is not a ... You have up to 2 years of experience or relevant internships. * AI-forward: You already build with ...

Atonom

AI Revenue Engineer

Provo, UT · On-site

$60K - $90K/yr

Join us as we build the infrastructure for the next generation of work. Role This is not a ... You have up to 2 years of experience or relevant internships. * AI-forward: You already build with ...

Atonom

AI Revenue Engineer

Provo, UT

Join us as we build the infrastructure for the next generation of work. Role This is not a ... You have up to 2 years of experience or relevant internships. * AI-forward: You already build with ...

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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 Utah?

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

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

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

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

Internship Ai Infrastructure Engineer jobs near you

Network Engineer, AI Infrastructure Repair

Meta

Eagle Mountain, UT

$193K/yr

Full-time

Re-posted 15 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

137th of 245 rated software companies

Job description

Meta is building the next generation of AI infrastructure to power large-scale machine learning workloads, and the reliability of that infrastructure depends on reliable, high-performance network engineering. In this role, you will lead the strategy and execution for AI network repair and remediation programs, ensuring that the high-performance fabrics underpinning Meta's AI training and inference clusters remain operational, resilient, and optimized. You will drive cross-functional initiatives spanning network deployment, fault diagnosis, and repair automation across Meta's AI data center environments, shaping the systems and processes that keep AI infrastructure at scale.
Network Engineer, AI Infrastructure Repair Responsibilities:
  • Define and drive the long-term strategy for AI network repair and remediation programs across large-scale data center environments supporting machine learning workloads
  • Lead root cause analysis and resolution of complex network faults affecting high-performance AI training and inference fabrics, including RDMA, high-speed Ethernet, and optical interconnect layers
  • Develop and champion novel approaches to network fault detection, automated remediation, and repair workflow optimization for AI cluster infrastructure
  • Partner with hardware, software, and data center operations teams to align network repair programs with AI infrastructure deployment roadmaps and capacity plans
  • Establish and refine operational frameworks, runbooks, and tooling for network repair at scale, reducing mean time to repair across AI fabric environments
  • Identify systemic reliability risks in AI network infrastructure and drive cross-functional initiatives to address them before they impact production workloads
  • Influence the design of next-generation AI network architectures by contributing repair and reliability insights to hardware and topology decisions
  • Leverage AI-driven analytics and automation tools to redesign repair workflows, accelerating fault identification and resolution across distributed network environments
  • Build and maintain strategic relationships with internal engineering, operations, and vendor partners to ensure repair programs scale with AI infrastructure growth
  • Communicate program status, risk, and strategic recommendations to engineering leaders and cross-functional stakeholders through structured reporting and executive briefings

Minimum Qualifications:
  • Experience influencing technical direction and organizational strategy through data-driven analysis, written proposals, and stakeholder alignment across engineering and operations teams
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Experience leading cross-functional programs that span network operations, hardware deployment, and infrastructure reliability at data center scale
  • Experience developing and driving strategy for network fault management, repair automation, or remediation programs in production environments
  • Experience designing, deploying, or operating high-speed network fabrics used in AI or machine learning infrastructure, including technologies such as RDMA over Converged Ethernet, InfiniBand, or high-density optical interconnects
  • 12+ years of experience in network engineering, with a focus on large-scale data center or high-performance computing network environments

Preferred Qualifications:
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Experience with network telemetry platforms, observability tooling, or AI-assisted anomaly detection applied to large-scale fabric environments
  • Experience building or scaling repair operations programs, including workforce planning, tooling development, and process standardization across multiple data center sites
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Track record of contributing to network hardware or topology design reviews, translating operational repair insights into upstream engineering improvements
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Familiarity with AI accelerator interconnect architectures and the network reliability requirements of distributed training workloads at hyperscale

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$193,000/year to $271,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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