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Ai Infrastructure Jobs in Silver Spring, MD (NOW HIRING)

Bigbear.ai

Full Stack Software Engineer

Columbia, MD

$114K - $228K/yr

In this role, you will support the AI infrastructure team by building and maintaining the platform that serves as the foundation for the customer's AI capabilities. You will focus on inference ...

Bigbear.ai

Full Stack Software Engineer

Columbia, MD · On-site

$114K/yr

In this role, you will support the AI infrastructure team by building and maintaining the platform that serves as the foundation for the customer's AI capabilities. You will focus on inference ...

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How much do ai infrastructure jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for ai infrastructure in Silver Spring, MD is $61.18, according to ZipRecruiter salary data. Most workers in this role earn between $49.71 and $71.30 per hour, depending on experience, location, and employer.

What is the difference between Ai Infrastructure vs Data Engineer?

AspectAi InfrastructureData Engineer
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of cloud platforms and AI toolsBachelor's in CS, Data Science, or related; programming and database skills
Work EnvironmentCloud environments, AI model deployment, infrastructure setupData pipelines, database management, data processing
Employer & Industry UsageTech companies, AI startups, cloud providersTech firms, finance, healthcare, e-commerce

Ai Infrastructure professionals focus on building and maintaining the hardware and software systems that support AI models, while Data Engineers develop and manage data pipelines and databases. Both roles require technical skills and often collaborate but serve different core functions within AI and data ecosystems.

How much do AI infrastructure engineers make?

AI infrastructure engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and hardware may earn higher salaries, often exceeding $180,000.

What are AI infrastructure jobs?

AI infrastructure jobs involve designing, building, and maintaining the hardware, software, and network systems necessary to support artificial intelligence applications. These roles often require knowledge of cloud computing, data centers, machine learning frameworks, and system optimization to ensure reliable and efficient AI model deployment and operation.

What are the key skills and qualifications needed to thrive in AI infrastructure?

To thrive in AI Infrastructure, you need expertise in software engineering, distributed systems, cloud platforms, and a solid understanding of machine learning workflows, often supported by degrees in computer science or related fields. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud services (AWS, GCP, Azure), as well as experience with CI/CD pipelines and monitoring systems, is essential. Strong problem-solving abilities, effective communication, and adaptability help professionals excel in cross-functional teams and rapidly evolving environments. These skills and qualities are crucial for building scalable, reliable systems that power AI applications and support organizational innovation.

What are common challenges faced by professionals working in AI infrastructure roles, and how can they be addressed?

Professionals in AI Infrastructure roles often encounter challenges related to scalability, system reliability, and integration with existing IT environments. Managing rapidly growing datasets and ensuring seamless deployment of machine learning models can be complex, requiring robust automation and monitoring tools. Collaboration with data scientists, software engineers, and DevOps teams is critical to ensure infrastructure meets the evolving needs of AI projects. Staying updated with the latest cloud technologies and best practices can help address these challenges and drive successful AI implementations.

What is AI infrastructure?

AI infrastructure refers to the combination of hardware, software, and cloud-based solutions that support the development, deployment, and scaling of artificial intelligence applications. It includes components such as GPUs, CPUs, storage systems, networking, data management tools, and machine learning frameworks. The goal of AI infrastructure is to provide the computational power and resources needed to train, test, and run AI models efficiently, whether on-premises or in the cloud. Organizations invest in robust AI infrastructure to accelerate innovation, manage large datasets, and ensure the reliability of their AI systems.
What job categories do people searching Ai Infrastructure jobs in Silver Spring, MD look for? The top searched job categories for Ai Infrastructure jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Ai Infrastructure jobs? Cities near Silver Spring, MD with the most Ai Infrastructure job openings:
Ai Infrastructure jobs near you
Infographic showing various Ai Infrastructure job openings in Silver Spring, MD as of August 2026, with employment types broken down into 14% Internship, 72% Full Time, and 14% Part Time. Highlights an 79% In-person, 7% Hybrid, and 14% Remote job distribution, with an average salary of $127,261 per year, or $61.2 per hour.

Network Engineer, AI Infrastructure Repair

Meta

Ashburn, VA

$193K/yr

Full-time

Re-posted 2 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 242 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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