Production Systems Engineer, Fleet AI Systems

Skip to main content

Jobs

Teams

Career Programs

Working at Meta

Blog

Podcasts

Jobs

Production Systems Engineer, Fleet AI Systems

Production Systems Engineer, Fleet AI Systems

Austin, TX +1 location

Engineering

+ 2 more

Apply now

Meta is seeking a Production Systems Engineer to lead the reliability, scalability, and operational excellence of our AI infrastructure fleet. This role sits at the intersection of large-scale AI compute systems and production engineering, supporting the hardware and software stack that powers Meta's AI training and inference workloads across tens of thousands of accelerators and servers.

You will drive the strategy for fleet health, automated diagnostics, and lifecycle management of AI-optimized hardware, partnering closely with hardware design, silicon, software, and data center operations teams to ensure our AI systems are production-ready and operating at peak efficiency.

Production Systems Engineer, Fleet AI Systems Responsibilities

• Define and drive the long-term technical strategy for fleet health monitoring, automated remediation, and lifecycle management of AI compute infrastructure at hyperscale
• Lead cross-functional initiatives spanning hardware design, firmware, systems software, and data center operations to bring new AI server platforms from pre-production validation through mass deployment
• Architect and oversee development of large-scale test automation frameworks for AI accelerator systems, covering GPU, TPU, and custom silicon configurations across diverse fleet topologies
• Establish organizational standards for root cause analysis methodologies, failure mode classification, and escalation workflows for AI system incidents at fleet scale
• Drive vendor and partner engagement on hardware specifications, firmware quality, and test methodology improvements to continuously raise the reliability bar for AI infrastructure
• Develop and champion data-driven visibility platforms that surface fleet health signals, predictive failure indicators, and capacity risk across AI training and inference clusters
• Lead ambiguous, high-impact investigations into systemic hardware and software failures affecting AI workload availability, producing durable solutions and documented learnings
• Mentor and provide technical direction to other engineers across the production systems organization, shaping engineering practices and raising the collective capability of the team
• Collaborate with capacity engineering and AI platform teams to translate fleet reliability requirements into hardware procurement, qualification, and deployment criteria
• Influence the roadmap of internal tooling and automation systems to reduce mean time to detection and resolution for AI fleet incidents at scale

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of experience in production systems engineering, server hardware support, or infrastructure reliability engineering at hyperscale
• 12+ years of experience troubleshooting and root-causing failures across the full hardware and software stack, including CPUs, accelerators, memory, networking, storage, firmware, and operating systems
• Experience leading large-scale technical programs across hardware, firmware, and software engineering organizations with demonstrated organizational impact
• Experience designing and implementing automated diagnostics, test frameworks, or remediation systems for large server fleets
• Experience with Linux systems administration and scripting or programming in Python or equivalent languages for infrastructure tooling

Preferred Qualifications

• Experience supporting AI training or inference infrastructure, including GPU clusters, high-speed interconnects such as InfiniBand or RoCE, and AI accelerator hardware at fleet scale
• Experience engaging directly with silicon vendors or ODMs on firmware qualification, failure analysis, and hardware specification development for AI compute systems
• Experience in post-production hyperscale environments managing full hardware lifecycle progressions for AI or HPC server platforms
• Experience with predictive fleet health modeling, telemetry pipelines, or data visualization platforms applied to large-scale hardware operations

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.

For those who live in or expect to work from California if hired for this position, please click here for additional information.

United States of America: $208,000/year to $289,000/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.

Equal Employment Opportunity

Meta is proud to be an Equal Employment Opportunity employer.

We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

You may view our Equal Employment Opportunity notice here .

Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form .

Apply for this job

Take the first step toward a rewarding career at Meta. Apply now

APPLY NOW

Find your role

Explore jobs that match your skills and experience. Search by technology, team or location to find an opening that’s right for you.

View jobs

Meta AI

Recruiters can view your conversations with AI. Using AI is optional and does not impact the outcome of your application process. Learn more

about AI usage and settings.

Sign up

to ask follow-up questions

Job Search

Technology Teams

Artificial Intelligence Creative Infrastructure Metaverse and Wearables Product and Program Management Research and Data Security Software Engineering

Business Teams

Business Operations Partnerships Sales and Marketing

Career Programs

Research Accelerate Eng Talent Students and Grads Rotational Programs

Working at Meta

Accessiblity and Engagement Benefits Culture Hiring Process

My account

Career profile Account settings Messages

Meta Careers Blog

Meta Tech Podcasts

About us

About Meta

Media gallery Brand resources For investors Looking for contractor roles?

Job Search

Technology Teams

Artificial Intelligence

Creative

Infrastructure

Metaverse and Wearables

Product and Program Management

Research and Data

Security

Software Engineering

Business Teams

Business Operations

Partnerships

Sales and Marketing

Career Programs

Research

Accelerate Eng Talent

Students and Grads

Rotational Programs

Working at Meta

Accessiblity and Engagement

Benefits

Culture

Hiring Process

My account

Career profile

Account settings

Messag