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Internship Ai Infrastructure Engineer Jobs in Georgia

Senior AI Engineer - SFL Scientific

Atlanta, GA · On-site

$100K - $138K/yr

Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns * Define and lead technology proof of concepts to ensure feasibility of new data and cloud ...

Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns * Define and lead technology proof of concepts to ensure feasibility of new data and cloud ...

If you want to do high-impact AI infrastructure work in enterprise software, we'd love to hear from you. About the Role The Workday AI Tools team is looking for a software engineer who's excited to ...

DevOps Expert - Remote

Atlanta, GA · Remote

$30 - $80/hr

Remote Job Overview We are seeking experienced Developer & Infrastructure Experts to evaluate AI-powered workflows across software development, cloud infrastructure, DevOps, SRE, and platform ...

Senior AI Software Engineer

Atlanta, GA · On-site

$117K - $155K/yr

The Senior Software Engineer work assignments involve moderately complex to complex issues where ... Infrastructure and MLOps: Contribute to AI infrastructure design, deployment automation, and ...

Senior AI Software Engineer

Atlanta, GA · On-site

$117K - $155K/yr

The Senior Software Engineer work assignments involve moderately complex to complex issues where ... Infrastructure and MLOps: Contribute to AI infrastructure design, deployment automation, and ...

Senior AI Software Engineer

Atlanta, GA · On-site

$117K - $155K/yr

The Senior Software Engineer work assignments involve moderately complex to complex issues where ... Infrastructure and MLOps: Contribute to AI infrastructure design, deployment automation, and ...

AI DevEx Engineer

Alpharetta, GA · On-site

$95K - $130K/yr

AI DevEx Engineer Overview: We are looking for a pragmatic and forward-thinking AI DevEx Engineer ... NET and React) to ensure scalability, security, and performance of our AI infrastructure. * Process ...

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure.

Showing results 41-60

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:

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

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:

Infographic showing various Internship Ai Infrastructure Engineer job openings in Georgia as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution.

Software Engineer, AI/Machine Learning, PhD, Early Career, 2027 Start

Google Inc.

Atlanta, GA • On-site

$147 - $210/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

48th of 247 rated software companies


Job description

Software Engineer, AI/Machine Learning, PhD, Early Career, 2027 Start Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

info_outline X In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Atlanta, GA, USA; Kirkland, WA, USA; Madison, WI, USA; Mountain View, CA, USA; New York, NY, USA; Raleigh, NC, USA; Durham, NC, USA; San Bruno, CA, USA; Seattle, WA, USA.
  • PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field, or equivalent practical experience.

Experience in Machine Learning or Artificial Intelligence.

Preferred qualifications:
  • Research experience in designing, developing, or applying ML/AI systems or applications in a large-scale distributed environment.
  • Experience in designing, training, or refining complex ML/AI models.
  • Experience in building a stack for an AI-powered application, including data ingestion and processing pipelines, building APIs, and connecting the model to a user-facing interface.
  • Familiarity with model architectures (CNNs, NLP Transformers, Diffusion/Vision Transformers).
  • Experience developing with Rust and modern deep learning frameworks such as PyTorch, JAX, or TensorFlow.
  • Availability to start in a full-time role in 2027.
About the job

Google's engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at a massive scale. You'll be at the forefront of innovation, developing systems and AI and Machine Learning solutions.

As a PhD graduate, your research expertise is invaluable to us. Explore a variety of projects, collaborate with various teams, and contribute to products that are changing the world, across many product areas, including AI & Infrastructure , Cloud , YouTube , Search , Ads and more!

Our engineering teams include thousands of PhDs who bring their deep knowledge and research experience to enhance our systems and products. As a Google PhD Software Engineer, you will work on critical projects, with many opportunities to learn and follow your interests. We expect our engineers to be creative and versatile, leading and identifying new problems to push the field and Google technology forward.

Google offers you exciting opportunities as it is one of the world’s leading producers and consumers of ML and AI technology, with decades of experience in designing, deploying, and using ML software and custom ML hardware infrastructure at massive scale.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

About the job

Google's engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at a massive scale. You'll be at the forefront of innovation, developing systems and AI and Machine Learning solutions.

As a PhD graduate, your research expertise is invaluable to us. Explore a variety of projects, collaborate with various teams, and contribute to products that are changing the world, across many product areas, including AI & Infrastructure , Cloud , YouTube , Search , Ads and more!

Our engineering teams include thousands of PhDs who bring their deep knowledge and research experience to enhance our systems and products. As a Google PhD Software Engineer, you will work on critical projects, with many opportunities to learn and follow your interests. We expect our engineers to be creative and versatile, leading and identifying new problems to push the field and Google technology forward.

Google offers you exciting opportunities as it is one of the world’s leading producers and consumers of ML and AI technology, with decades of experience in designing, deploying, and using ML software and custom ML hardware infrastructure at massive scale.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .

  • Collaborate or lead on team projects to carry out design, analysis, and development of advanced ML systems across the stack using your research expertise.
  • Support building end-to-end ML Systems that involves working across the full stack, from low-level hardware acceleration and compiler optimizations to high-level model architecture and production APIs, transforming your research expertise into robust, scalable products.
  • Optimize complex system performance by analyzing and fixing performance bottlenecks, memory inefficiencies, and errors in production systems to meet stringent customer goals.
  • Elevate engineering excellence by writing well-tested code, conducting code reviews and fostering a culture of quality by advocatingbest engineering practices.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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