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Entry Level Ai Infrastructure Engineer Jobs (NOW HIRING)

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 ...

Crowe LLP

AI Infrastructure Engineer

Costa Mesa, CA · On-site

$115K - $151K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Indianapolis, IN · On-site

$102K - $134K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

New York, NY · On-site

$117K - $154K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Cleveland, OH · On-site

$104K - $136K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Nashville, TN · On-site

$103K - $136K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

San Jose, CA · On-site

$126K - $165K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Sacramento, CA · On-site

$114K - $150K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Grand Rapids, MI · On-site

$103K - $135K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Oakbrook Terrace, IL · On-site

$108K - $141K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Dallas, TX · On-site

$106K - $139K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Charlotte, NC · On-site

$105K - $137K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Denver, CO · On-site

$110K - $145K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

South Bend, IN · On-site

$105K - $138K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Miami, FL · On-site

$102K - $134K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Atlanta, GA · On-site

$103K - $135K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Chicago, IL · On-site

$110K - $145K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Hartford, CT · On-site

$108K - $142K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

Crowe LLP

AI Infrastructure Engineer

Columbus, OH · On-site

$103K - $136K/yr

As an AI Infrastructure Engineer, you are a deep technical contributor with subsystem ownership and notable technical influence. Your role will be crucial in ensuring that the AI solutions you ...

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Entry Level Ai Infrastructure Engineer information

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$46.5K

$127.1K

$182K

How much do entry level ai infrastructure engineer jobs pay per year?

As of Jul 20, 2026, the average yearly pay for entry level ai infrastructure engineer in the United States is $127,066.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $141,000.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level positions in artificial intelligence, such as senior AI engineers, research directors, or executive roles, which offer compensation in that range including salary, bonuses, and stock options. Entry-level AI infrastructure engineers usually earn significantly less, with salaries often starting in the low six figures depending on experience and location.

Can you become an AI engineer with no experience?

Becoming an AI infrastructure engineer typically requires some background in programming, data structures, and machine learning concepts. While prior experience is helpful, entry-level roles often accept candidates who demonstrate strong technical skills, a willingness to learn, and relevant certifications or coursework in AI and cloud platforms. Building a portfolio through projects and gaining familiarity with tools like Python, TensorFlow, or cloud services can improve chances of entry without prior professional experience.

What engineer makes $500,000 a year?

While most entry-level AI infrastructure engineers do not earn that level of salary, senior AI or machine learning engineers with extensive experience, specialized skills, and advanced certifications can reach or exceed $500,000 annually, especially in high-demand industries or companies with competitive compensation packages. Such roles often require expertise in cloud platforms, large-scale data processing, and deep learning frameworks.

What is the difference between Entry Level Ai Infrastructure Engineer vs Data Engineer?

AspectEntry Level Ai Infrastructure EngineerData Engineer
Required CredentialsBachelor's in CS, EE, or related; familiarity with AI toolsBachelor's in CS, Data Science, or related; experience with databases
Work EnvironmentAI/ML teams, cloud platforms, infrastructure setupData pipelines, database management, cloud services
Industry UsageTech companies, AI startups, research labsFinance, healthcare, tech firms, data-driven industries

Entry Level Ai Infrastructure Engineers focus on building and maintaining AI infrastructure, including cloud and hardware setups, while Data Engineers primarily develop data pipelines and manage data storage. Both roles require technical skills and often overlap in cloud environments, but they serve different core functions within data and AI projects.

How to become an AI infrastructure engineer?

To become an AI infrastructure engineer, you should have a strong foundation in computer science, including knowledge of cloud platforms, networking, and hardware systems. Gaining skills in programming languages like Python and understanding AI frameworks, along with certifications in cloud services such as AWS or Azure, can enhance your qualifications. Practical experience with deploying and managing AI models and infrastructure is also essential.
More about Entry Level Ai Infrastructure Engineer jobs
What cities are hiring for Entry Level Ai Infrastructure Engineer jobs? Cities with the most Entry Level Ai Infrastructure Engineer job openings:
What are the most commonly searched types of Ai Infrastructure Engineer jobs? The most popular types of Ai Infrastructure Engineer jobs are:
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What job categories do people searching Entry Level Ai Infrastructure Engineer jobs look for? The top searched job categories for Entry Level Ai Infrastructure Engineer jobs are:
Entry Level Ai Infrastructure Engineer jobs near you
Infographic showing various Entry Level Ai Infrastructure Engineer job openings in the United States as of July 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $127,066 per year, or $61.1 per hour.

AI Infrastructure Engineer

MeshyAI

Sunnyvale, CA • On-site

$125K - $164K/yr

Full-time

Re-posted 3 days ago

Job description

Job Summary:
MeshyAI is a leading 3D generative AI company headquartered in Silicon Valley, focused on transforming the content creation pipeline. 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 systems.
Responsibilities:
• Responsible for the design, development, and optimization of core capabilities for the AI inference platform, including key modules such as inference services, task scheduling, service orchestration, elastic scaling, and release governance.
• Participate in the development of CPU/GPU resource management systems to optimize stability, resource utilization, and cost efficiency in scenarios where online inference and training tasks are run on the same cluster.
• Drive the unified management and scheduling of GPU resources, and explore the practical implementation of capabilities such as MIG, MPS, time-sharing, and virtualization in real-world business operations.
• Continuously optimize the throughput, latency, and availability of the inference pipeline, refining engineering quality in complex inference pipelines, multi-model collaboration, and high-concurrency scenarios.
• Focus on R&D efficiency, resource and cost management, online stability, and disaster recovery architecture design to drive the company’s continuous evolution in performance, reliability, and maintainability.
• Explore AI-native infrastructure and automated operations to make infrastructure smarter and more user-friendly, supporting the company’s rapid expansion during its startup phase.
Qualifications:
Required:
• Bachelor’s degree or higher; majors in Computer Science, Software Engineering, Artificial Intelligence, Telecommunications, or related fields are preferred.
• 1 to 3 years of experience in backend development, infrastructure, cloud-native platforms, machine learning platforms, or AI platforms.
• Proficiency in at least one of Go or Python, with solid software engineering skills and a strong commitment to code quality.
• Understanding of fundamental principles in Linux, operating systems, computer networks, and distributed systems; ability to independently identify and resolve complex engineering issues.
• Practical development experience with Kubernetes, Docker, microservices, or distributed systems, with a basic understanding of production system stability.
• Real-world project experience in areas such as model inference, task orchestration, resource scheduling, and service stability—beyond mere conceptual understanding.
• Self-motivated, curious, and a fast learner; willing to take on greater ownership and broader responsibilities in a startup environment, while continuously learning and quickly adopting new technologies.
Preferred:
• Experience with GPU inference platforms, Kubernetes schedulers, Device Plugins, or related platform development.
• Familiarity with frameworks such as Ray and Ray Serve, or experience in developing and optimizing model serving, distributed inference, and task orchestration frameworks.
• Familiarity with solutions related to MIG, MPS, vGPU, partitioned GPUs, or GPU resource reuse, and experience balancing performance and stability.
• Engineering experience in observability, SRE, capacity planning, cost governance, canary deployments, and automated rollbacks.
• Open-source projects, technical blogs, personal projects (side projects), or other achievements that demonstrate learning agility and growth potential.
• Ongoing interest and hands-on experience in emerging areas such as AI infrastructure (AI Infra), inference systems, and AI agent toolchains.
Company:
Meet the world's most popular and intuitive free AI 3D model generator. Founded in 2021, the company is headquartered in Sunnyvale, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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