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Internship Ai Infrastructure Engineer Jobs in Virginia

AI Infrastructure Engineer

Chantilly, VA · On-site

$110K - $144K/yr

AI Infrastructure Engineer Top Secret or TS/SCI is required to start $200K to $250K Chantilly, VA What You'll Do * Deploy and optimize self-hosted LLM inference servers (vLLM, Ollama, and similar)

AI Infrastructure Engineer Top Secret or TS/SCI is required to start $200K to $250K Chantilly, VA What You'll Do * Deploy and optimize self-hosted LLM inference servers (vLLM, Ollama, and similar)

Cloud Infrastructure Engineer

Mclean, VA · On-site

$57.25 - $76.50/hr

Residency All applicants must currently reside in the United States Overview BigBear.ai is hiring Cloud Infrastructure Engineers to build and maintain the underlying government cloud infrastructure ...

Residency All applicants must currently reside in the United States Overview BigBear.ai is hiring Cloud Infrastructure Engineers to build and maintain the underlying government cloud infrastructure ...

Cloud Infrastructure Engineer

Mclean, VA · Remote

$142K - $190K/yr

Overview BigBear.ai is hiring Cloud Infrastructure Engineers to build and maintain the underlying government cloud infrastructure that supports the program's polyglot database stack. Working ...

Cloud Infrastructure Engineer

Arlington, VA · On-site

$123K - $162K/yr

... an AI-enabled logistics command and control platform. The role involves designing and operating ... Required : • 5+ years of experience in DevOps, SRE, infrastructure or software engineering roles ...

Leidos is seeking an AI & Security Infrastructure Integration Engineer to join our team in Alexandria, VA. This is a hybrid position allowing partial telework, but the majority of the time is spent ...

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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 Virginia?

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

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

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

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

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

Infographic showing various Internship Ai Infrastructure Engineer job openings in Virginia as of August 2026, with employment types broken down into 71% Full Time, 27% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

AI Infrastructure Engineer

Bright Vision Technologies

Reston, VA • On-site

$100 - $150/hr

Other

Posted 7 days ago


Job description

AI Infrastructure Engineer-Remote

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: AI Infrastructure Engineer

Location: 100% Remote (United States)

Position Type: Full-time, Direct W2

Salary Range: $100,000–$150,000 Annually

Experience: 6+ years

Sponsorship: U.S. Citizens, Green CardHolders, EADHolders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

We are seeking an AI Performance Optimization Engineer to focus on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems. The role spans the full stack from low-level kernel optimization to distributed system tuning, requiring deep understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization. The ideal candidate has demonstrated an impact on production of AI workloads, with strong instrumentation and measurement discipline that enables rigorous, data-driven optimization decisions. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.

Required Qualifications
  • Bachelor's or master's degree in computer science, Computer Engineering, or related field.
  • Six or more years of experience in performance engineering, ML systems, or HPC.
  • Strong proficiency in Python and C++.
  • Hands-on experience optimizing deep learning workloads on modern GPUs.
  • Deep understanding of distributed training and inference techniques.
  • Experience with profiling tools across CPU, GPU, and distributed systems.
  • Familiarity with model compression techniques and their accuracy implications.
  • Strong grasp of memory hierarchies, communication primitives, and parallelism strategies.
  • Excellent measurement, debugging, and analytical reasoning skills.
  • Strong communication and collaboration skills.
Preferred Qualifications
  • Experience optimizing LLM inference at production scale.
  • Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
  • Familiarity with custom kernel authoring in Triton or CUTLASS.
  • Experience with FinOps for AI workloads.
  • Publications or talks on AI systems performance.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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