xAI
Understand the Universe. We are a team of AI technologists and business leaders on a mission to build AI systems that can help humanity understand the world better. https://x.ai/careers
Open Positions at xAI
51 open positions
Build and ship high-impact advertising products for X Ads, spanning backend systems, distributed infrastructure, targeting, optimization, measurement, and AI-powered features. This early-career role offers meaningful ownership on systems operating at massive scale.
Build and optimize the high-performance inference platform serving Grok at massive scale. This hands-on role spans distributed model-serving infrastructure, GPU-level optimization, reliability, and next-generation inference research.
Site Reliability Engineer responsible for campus-scale reliability across compute, network, storage, power, and cooling systems. The role leads major incident response, observability strategy, and cross-functional corrective action in a data center environment.
Build reliable backend and full-stack platforms that keep large-scale data center operations accurate, auditable, and efficient. You’ll work directly with SiteOps and NOC users on workflows, integrations, dashboards, and operational data systems.
Build and operate high-performance search infrastructure that supports massive indexing and query workloads. You’ll shape search internals, improve reliability and performance, and lead incident response for mission-critical systems.
Build scalable APIs and platform systems that connect developers and automated agents with X data and functionality. You will help evolve a highly available developer ecosystem serving customers worldwide.
Build the Linux-based operating system, device drivers, and production platform software powering a supercomputer network fabric. This hands-on role spans kernel and systems programming, hardware bring-up, debugging, reliability, and collaboration with hardware teams.
Build and own the evaluation platform that measures AI model capabilities, improves datasets, and diagnoses agent failures. This hands-on role combines software engineering, research infrastructure, and exceptional product judgment.
Build the high-performance ML infrastructure powering large-scale recommendations, from GPU compute and training frameworks to data pipelines and inference systems. This hands-on role combines systems engineering, machine learning platforms, and close collaboration with modeling teams.
Build the distributed platform infrastructure behind a large-scale AI supercomputing cluster, working across systems software, Kubernetes, Linux, networking, and performance optimization. This hands-on role combines low-level systems engineering with production-grade infrastructure operations.
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