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Internship Ai Infrastructure Engineer Jobs in Georgia

Truist

Sn. Infrastructure Engineer

Atlanta, GA · On-site

$103K - $135K/yr

Truist is a financial services company seeking a Senior Infrastructure Engineer. The role involves ... with AI coding agents and assistants (e.g., GitLab Duo, GitHub Copilot, or similar) as ...

Apex Systems

Azure Infrastructure Engineer

Cumming, GA · On-site

$95K - $125K/yr

Job#: 3047058 Azure Infrastructure Engineer Location: REMOTE Role Overview The Enterprise ... By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails ...

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RoadSync

Infrastructure Engineer

Atlanta, GA · Hybrid

$103K - $135K/yr

We are embracing AI-assisted development workflows and seeking engineers who can leverage tools ... Fluency with infrastructure-as-code in Terraform or AWS CDK, including module design, state ...

Socket.dev

Infrastructure Engineer

Atlanta, GA · On-site

$120 - $170/hr

We are embracing AI-assisted development workflows and seeking engineers who can leverage tools ... Fluency with infrastructure-as-code in Terraform or AWS CDK, including module design, state ...

Deloitte

Azure/Databricks Infrastructure Engineer

Atlanta, GA · On-site

$53.50 - $71.75/hr

Join Deloitte's AI & Engineering practice and help organizations modernize enterprise cloud and data platforms on Azure. As an Azure/Databricks Infrastructure Engineer, you will design, implement ...

RoadSync

Infrastructure Engineer

Atlanta, GA · On-site

$120 - $170/hr

We are embracing AI-assisted development workflows and seeking engineers who can leverage tools ... Fluency with infrastructure-as-code in Terraform or AWS CDK, including module design, state ...

Deloitte

Azure/Databricks Infrastructure Engineer

Atlanta, GA · On-site

$53.50 - $71.75/hr

Join Deloitte's AI & Engineering practice and help organizations modernize enterprise cloud and data platforms on Azure. As an Azure/Databricks Infrastructure Engineer, you will design, implement ...

Flight Centre Travel Group (usa) Inc

$92K - $125K/yr

Senior Cloud Infrastructure Engineer - South Bank, QLD Apply now Refer a friend Job no: 531618SS ... You'll be embedded in our Supply AI & Data team while reporting to the Infrastructure Manager ...

Deloitte

AI Datacenter Associate VP

Atlanta, GA · 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 ...

PGTEK

HPC Infrastructure Engineer - Travel role

Atlanta, GA · On-site

$90K - $100K/yr

Infrastructure / High-Performance Computing (HPC) Support Engineer We are seeking an Infrastructure ... Experience supporting High-Performance Computing (HPC), AI, GPU, or clustered compute environments

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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 Georgia?

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

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

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

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

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

Cities in Georgia 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 Georgia as of August 2026, with employment types broken down into 71% Full Time, 19% Part Time, 7% Contract, and 3% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

AI/ML Ops & Infrastructure Engineer - Q126

R2 Technologies Corporation

Alpharetta, GA • On-site

$105K - $137K/yr

Full-time

Re-posted 22 days ago

Job description

Overview:
Job Title: AI/ML Ops & Infrastructure Engineer
Company: R2 Technologies
Location: Alpharetta, GA (Hybrid / Remote Options Available)
Employment Type: Full-Time / Contractual
About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we have built a reputation as a trusted partner for IT staffing excellence and cutting-edge digital product innovation. We are driven by innovation and operate on a simple philosophy: "We deliver what we promise, and we promise only what we can deliver." Beyond providing top-tier IT talent, R2 builds cutting-edge proprietary solutions like SmartEnt-an Enterprise AI & IoT Intelligence Platform utilizing advanced NLP and AI technologies. By partnering closely with our clients, we deliver technology-driven outcomes that are realistic, measurable, and impactful.
Job Summary: The shift from classical Machine Learning to Generative AI requires a new breed of infrastructure engineering. R2 Technologies is looking for an AI/ML Ops & Infrastructure Engineer to build and manage the operational backbone for our advanced LLM and agentic systems. You will transition beyond basic CI/CD to implement full-lifecycle LLMOps-managing foundation models, fine-tuned adapters, routing logic, and guardrails. Your work will ensure that our AI solutions, including SmartEnt, run with high performance, optimal GPU utilization, and rigorous compliance.
Key Responsibilities: * Design and maintain highly scalable LLMOps pipelines for continuous integration, evaluation, and deployment of machine learning models and AI agents.
  • Deploy and manage containerized AI applications and model inference servers (e.g., vLLM, Ray Serve, NVIDIA Triton) on Kubernetes across multi-cloud environments (AWS, GCP, Azure).
  • Implement comprehensive observability and trace-level logging for multi-step agentic workflows using platforms like LangSmith, W&B Weave, or MLflow.
  • Automate infrastructure provisioning and monitoring using tools like Terraform and agent-driven workflows (e.g., n8n, GitHub Actions).
  • Optimize GPU computing costs, latency, and token usage for high-traffic AI inference endpoints.
  • Enforce security guardrails, toxic output filtering, and robust access policies within the AI deployment infrastructure.
  • Actively utilize AI-assisted coding tools (Copilot, Cursor) to automate infrastructure-as-code (IaC) and streamline Kubernetes management.

Qualifications: *3 years of hands-on experience in MLOps, DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure.
  • Strong proficiency in containerization and orchestration (Docker, Kubernetes).
  • Experience with ML/LLM operational platforms (MLflow, Weights & Biases, Databricks Mosaic AI, or SageMaker).
  • Familiarity with serving open-source or fine-tuned LLMs and optimizing inference performance.
  • Proven experience or strong familiarity working alongside AI coding assistants to enhance productivity.
  • Scripting/programming skills in Python and bash, along with experience in CI/CD automation.
  • Passion for the evolving landscape of AI infrastructure, cost-optimization (FinOps), and system reliability.

Skills:
Nvidia,Infrastructure

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