In this role, you will push the boundaries of container orchestration far beyond existing systems like Kubernetes, manage exascale compute resources, optimize for high-performance training runs and production serving, and collaborate closely with research and systems teams to deliver reliable, ultra-scalable infrastructure that enables xAI's next-generation models and applications.

Responsibilities include building and managing massive-scale clusters, designing, developing, and extending an in-house container orchestration platform, collaborating with research teams to architect and optimize compute clusters, profiling, debugging, and resolving complex system-level performance bottlenecks, and owning end-to-end infrastructure initiatives.

To succeed in this role, you will need deep expertise in virtualization technologies and advanced containerization/sandboxing, strong proficiency in systems programming languages such as C/C++ and Rust, and proven track record profiling, debugging, and optimizing complex system-level performance issues.

Preferred skills and experience include experience in Linux kernel development, hypervisor extensions, or low-level system programming for compute-intensive workloads, operating or designing large-scale AI training/inference clusters, and familiarity with performance tools, tracing, and debugging in production distributed environments.

XML job scraping automation by YubHub

Responsibilities:

• Build and manage massive-scale clusters to host, persist, train, and serve AI workloads with extreme reliability and performance.
• Design, develop, and extend an in-house container orchestration platform that achieves superior scalability, isolation, resource efficiency, and fault-tolerance compared to off-the-shelf solutions.
• Collaborate with research teams to architect and optimize compute clusters specifically for large-scale training runs, inference services, and real-time applications.
• Profile, debug, and resolve complex system-level performance bottlenecks, resource contention, scheduling issues, and reliability problems across the full stack.
• Own end-to-end infrastructure initiatives with first-principles design, rigorous testing, automation, and continuous optimization to support frontier AI compute demands.

Basic Qualifications:

• Deep expertise in virtualization technologies (KVM, Xen, QEMU) and advanced containerization/sandboxing (Kata, Firecracker, gVisor, Sysbox, or equivalent).
• Strong proficiency in systems programming languages such as C/C++ and Rust.
• Proven track record profiling, debugging, and optimizing complex system-level performance issues, with deep knowledge of Linux kernel internals, resource management, scheduling, memory management, and low-level engineering.
• Hands-on experience building or significantly enhancing distributed compute platforms, orchestration systems, or high-performance infrastructure at scale.

Preferred Skills and Experience:

• Experience in Linux kernel development, hypervisor extensions, or low-level system programming for compute-intensive workloads.
• Proven track record operating or designing large-scale AI training/inference clusters (GPU/TPU scale).
• Experience with custom runtimes, isolation techniques, or bespoke platforms for specialized AI compute.
• Familiarity with performance tools, tracing, and debugging in production distributed environments.

Compensation and Benefits:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

XML job scraping automation by YubHub