Software Engineer - Storage (Technical Leadership)

Meta

$150K — $180K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science or equivalent experience
  • 8+ years coding experience in C, C++, Java and/or C#
  • Experience leading industry-impact storage infrastructure projects
  • Proven mentorship and influence skills across teams
  • Track record planning multi-year project roadmaps
  • 8+ years building distributed storage systems or server applications
  • Strong communication skills for cross-functional collaboration

Responsibilities

  • Communicate complex storage system features and architectures clearly
  • Drive technical direction to enhance storage performance and reliability
  • Design storage systems for high throughput and low latency in AI workloads
  • Lead performance improvement efforts for diverse storage use cases
  • Collaborate with leaders to boost team and organizational performance
  • Identify and promote innovative storage opportunities
  • Develop long-term technical strategy for storage infrastructure

Benefits

  • Flexible work hours and remote work options
  • Collaborative and innovative work environment
  • Opportunities for continuous learning and career advancement
  • Access to cutting-edge technology and tools
  • Strong focus on diversity and inclusion initiatives
Full Job Description
Meta is seeking an experienced Software Engineer to join the Storage Infrastructure team. Our storage systems power Meta's products at unprecedented scale, handling exabytes of data with sub-second latency while enabling the next generation of AI training workloads. We build and optimize distributed storage solutions that deliver high performance and reliability for both traditional web-scale serving and the demanding throughput requirements of large-scale AI/ML training pipelines. We are looking for candidates who share a proven commitment to tackling complexity in storage systems and building platforms that can scale through multiple orders of magnitude while meeting the unique performance characteristics required for AI infrastructure.

Responsibilities

Effectively communicate complex storage system features and architectures in detail
• Drive the team's goals and technical direction to pursue opportunities that improve storage performance, reliability, and efficiency at scale
• Design and optimize storage systems to meet the demanding throughput and latency requirements of AI training workloads
• Lead efforts to improve storage system performance for both serving and AI/ML training use cases
• Partner & collaborate with organization leaders to help improve the level of performance of the team & organization
• Identify new opportunities for storage innovation and influence the appropriate people for staffing/prioritizing these new ideas
• Lead long term technical strategy and roadmap for storage infrastructure across the company
• Suggest, collect and synthesize requirements and create an effective feature roadmap for storage systems

Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Experience leading storage infrastructure projects with industry-wide impact
• Vast experience communicating and working across functions to drive storage solutions
• Significant experience in mentoring/influencing engineers across organizations
• Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long term mission
• Experience in driving large cross-functional/industry-wide storage engineering efforts
• 8+ years coding experience in C, C++, Java and/or C#
• 8+ years of experience building distributed storage systems or server applications

Preferred Qualifications
• Experience and familiarity with transport protocols
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with server overload protection mechanisms
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Ability to debug gnarly performance issues in networking and kernel
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with operating system internals, filesystems, programming language design, compilers

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