1 day ago
Base Salary
$184k - $257k/yr
Responsibilities
- Set technical direction and lead the design, build, and operation of large-scale multi-tenant GPU, ML training, inference, rendering, and general compute infrastructure on Kubernetes.
- Drive cross-team and organization-level initiatives improving cluster reliability, scheduling efficiency, utilization, and scale, including datacenter and hardware migrations and expansions.
- Improve end-to-end cluster reliability through on-call participation, incident response, automation, and observability.
- Define and drive best practices for system design, testing, code health, and operational excellence.
- Partner with research and infrastructure teams to translate ML workload requirements into platform capabilities and influence architecture and technical decisions.
- Mentor engineers, review designs, and improve technical quality through code reviews, design guidance, and knowledge sharing.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 8+ years of professional software engineering experience, including technical leadership of complex cross-team infrastructure efforts.
- Experience building and maintaining production systems in Python and/or Go, C++, or a similar language.
- Experience designing, operating, and scaling large distributed systems in production, including reliability and on-call ownership.
- Hands-on experience running container orchestration such as Kubernetes at scale.
- Experience with GPU/ML training infrastructure, cluster or batch scheduling, distributed storage, or high-performance networking.
- Ability to drive ambiguous organization-level technical problems to resolution and set multi-quarter technical direction.
- Preferred qualifications include distributed or parallel storage systems, deep Linux systems experience, performance tuning, observability, GPU cluster operations, NCCL, high-performance networking, distributed ML training frameworks, Kubernetes operators and CRDs, batch schedulers, Hack or PHP, and responsible and ethical AI practices.
- Preferred qualifications also include experience integrating AI tools into workflows, prompt or context engineering, agent orchestration, and ongoing development of AI skills.
Benefits
- Base salary is $183,997/year to $257,000/year, plus bonus, equity, and benefits.
Categories
About Meta
Meta builds social platforms and communication apps—including Facebook, Instagram, WhatsApp, and Messenger—and develops AR/VR hardware and software such as Quest to power immersive computing. It monetizes primarily through advertising tools for businesses, with additional revenue from devices and services, and operates a massive global infrastructure. Founded in 2004 and headquartered in Menlo Park, California, Meta Platforms, Inc. is a public company traded on Nasdaq under the ticker META.