Meta Production Systems Engineer, AI Systems in Austin, Texas
Meta is seeking a Systems Engineer to join our Release to Production (RTP) team working on AI/ML initiatives. Our servers and data centers are the foundation upon which our rapidly scaling infrastructure operates efficiently to deliver our innovative services. The RTP team is responsible for the end-to-end Hardware Lifecycle of all Meta servers including prototyping of experimental HW, pre-production hands-on system and hardware debugging and stress testing, enabling production-ready system monitoring, automated provisioning and automated remediation of issues. RTP team also helps in exploring, developing and productizing high-performance software and hardware technologies for AI at datacenter scale. Production Systems Engineer, AI Systems in RTP work closely with HW/SW co-design teams, hardware designers, networking teams, system manufacturers, component vendors, capacity engineering, production engineering, production services, and data center operations teams to enable new systems that will be deployed in our production data centers. We also work across service and hardware architectures for new AI systems, build prototypes to demonstrate the value, enable go/no-go decisions and optimize these systems in production.
Production Systems Engineer, AI Systems Responsibilities:
Interface with external vendors and internal hardware, mechanical, power, thermal, manufacturing and software engineers to understand system architecture to develop and execute the test suites for various architectures
Leverage deep understanding HW/SW systems to execute full product life-cycles (prototyping, deployment, and support)
Champion engineering and operational excellence, establishing metrics and process for regular assessment and improvement
Develop visibility through data visualization and implement systemic solutions to hardware health issues
Proactively create experiments and tooling to detect and diagnose hardware/firmware/software health issues
Troubleshoot, diagnose and root cause of system failures and isolate the components/failure scenarios while working with internal & external stakeholders
Drive necessary discussion with external and internal teams on test specification and methodologies to improve test quality continuously
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
3+ years of work experience in one or more domains such as: ASIC development (Silicon design or bringup or characterization), compute (ARM, x86), AI-ML hardware/software (GPUs, TPUs)
Knowledge of server architecture and components across Compute/Storage/AI Systems
3+ years of experience with hardware development process and how to scope out test plans accordingly
Experience troubleshooting problems at system level, crossing across multiple components, as well as hardware/firmware/software boundaries
3+ years of experience support hardware design team (silicon design or datacenter platform design: compute, storage, etc.) in end-to-end product development cycles.
3+ years of experience in high-impact/high profile/at scale projects
3+ years of experience with one subset of the following AI systems: Accelerator (GPU/ASIC), Kernel development, Performance optimization (e.g., NVIDIA, AMD, Intel, or other misc accelerator), computer architecture, HPC communication libraries (e.g., NCCL, MPI), performance enablement, tracing, profiling and debugging.
Experience with architecture of disaggregated systems at scale
3+ years experience with IO and memory buses like PCIe, DDR
$124,000/year to $191,000/year + bonus + equity + benefits
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