Software Engineer, Systems

Meta is seeking a Software Engineer specializing in systems software to drive technical direction across large-scale infrastructure and platform engineering. The team responsible for the foundational runtime that powers containers and virtual machines across Meta’s compute fleet. This team builds the host-level systems that launch, manage, isolate, monitor, and terminate workloads. Its software coordinates workload artifacts and compute resources while enforcing performance, reliability, security, and resource-isolation boundaries. The runtime sits at a critical layer between applications and the underlying host infrastructure.

Responsibilities

• Define and drive the long-term technical vision and architecture for large-scale systems software, including platform services, runtime environments, and low-level infrastructure components
• Architect systems-level solutions that address performance, reliability, and scalability requirements across distributed infrastructure serving billions of users
• You will work on technically challenging systems at global scale, spanning Linux systems programming, container and virtual machine lifecycle management, resource control, workload isolation, performance, and fleet reliability
• The broader platform provides a common foundation for deploying and operating services across Meta’s infrastructure

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 8+ years of experience in systems software engineering, including design and implementation of operating system interfaces, runtime environments, distributed infrastructure, or low-level platform services
• Set and drive the technical direction for container runtime and isolation stack
• Improve fleet-wide efficiency and reliability of container-based workloads: resource enforcement, noisy-neighbor isolation, and density at millions-of-servers scale
• Extend runtime and isolation primitives to support AI training and inference workloads (accelerator isolation, large-memory and high-bandwidth jobs, gang-scheduled work)
• Partner with kernel, scheduler, capacity, and hardware teams on hardware-software co-design and multi-generational fleet transitions
• Mentor engineers, drive cross team design review, and represent teams container strategy within the Org

Preferred qualifications

• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience leading large-scale platform migrations or systems modernization efforts in high-availability production environments
• 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
• Experience with operating system internals such as scheduler design, memory subsystems, or kernel-userspace interfaces
• Experience with distributed systems consensus protocols such as Raft or Paxos, or building highly available and fault-tolerant infrastructure