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About the Role
Meta is seeking a Software Engineer specializing in systems software to drive technical direction across large-scale infrastructure and platform engineering. The team is responsible for the foundational runtime that powers containers and virtual machines across Meta’s compute fleet, building host-level systems that launch, manage, isolate, monitor, and terminate workloads.
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.
- 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.
- 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.
Requirements
- 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.
- 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.
Skills
- Systems software engineering
- Operating system interfaces
- Runtime environments
- Distributed infrastructure
- Low-level platform services
- Linux systems programming
- Container lifecycle management
- Virtual machine lifecycle management
- Resource control
- Workload isolation
- Performance
- Fleet reliability
- Responsible AI practices
- Ethical AI practices
- Risk assessment
- Bias mitigation
- Quality and accuracy reviews
- Platform migrations
- Systems modernization
- High-availability production environments
- AI tools integration
- Prompt engineering
- Context engineering
- Agent orchestration
- Emerging AI technologies
- Operating system internals
- Scheduler design
- Memory subsystems
- Kernel-userspace interfaces
- Distributed systems consensus protocols
- Raft
- Paxos
- Highly available infrastructure
- Fault-tolerant infrastructure
Experience Level
- 8+ years of experience
Education Level
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Salary/Compensations
- $183,997/year to $257,000/year
Benefits
- bonus
- equity
About the Company
- The broader platform provides a common foundation for deploying and operating services across Meta’s infrastructure.