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xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. The job is looking to solve the problem of building reliable and scalable AI infrastructure to support this mission.

Requirements

• Worked on large-scale, high-concurrent production serving.
• Worked on GPU inference engines.
• Worked on testing, benchmarking, and the reliability of inference services.
• Worked on designing and implementing CI/CD infrastructure.

Responsibilities

• Architect and implement scalable distributed infrastructure for model serving, such as load balancing, auto scaling, batch scheduling, and global KVcache systems.
• Ensure the reliability of inference services, targeting 100% uptime, a 0% error rate, and good tail performance, through proactive monitoring, fault-tolerant designs, and rigorous testing.
• Create custom tools to trace, replay, and fix issues or crashes across the entire stack, from cluster orchestration to GPU kernels.
• Benchmark and fine-tune inference engines to deliver optimal performance under diverse, production workloads.
• Develop robust CI/CD infrastructure to enable seamless endpoint deployment, image publishing, feature rollouts, and inference engine updates.

Other

• Candidates are expected to be located near the Bay Area or open to relocation.
• All engineers are expected to have strong communication skills.
• Work ethic and strong prioritization skills are important.
• Leadership is given to those who show initiative and consistently deliver excellence.
• All employees are expected to be hands-on and to contribute directly to the company’s mission.