Design and implement large-scale distributed systems for a supercomputing cluster, optimize low-level performance across GPUs, kernel, networking, and filesystems, collaborate on hardware-software co-design, maintain scalable reliable codebase, and build productivity tools.
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
- Design, build, and implement a large-scale distributed system that powers one of the world's largest supercomputing clusters.
- Dive into the low-level stack to profile, debug, and optimize performance across diverse systems, including GPUs, Linux kernel, networking, and filesystems, to achieve peak efficiency.
- Collaborate on hardware, software, and algorithm co-design to push the boundaries of AI training.
- Maintain and innovate on our codebase to ensure scalability and reliability.
- Develop tools to enhance team productivity and streamline workflows.
- Systems programming experience in C, C++, or Rust
- Computer systems fundamentals with a grasp of how computers execute code from transistors to high-level applications.
- Hands-on expertise with Kubernetes (K8s), including cluster architecture, pod lifecycle, networking (CNI), storage (CSI), service mesh, and production-grade operations
- Collaborate in a fast-paced, open environment to design and foundational systems.
- Strong debugging skills across the full stack — from kernel and OS up through container orchestration layers
- Deep knowledge of operating systems internals (process scheduling, memory management, file systems, and synchronization primitives)
- Proficiency in performance analysis, profiling, and low-level optimization techniques
- Solid understanding of computer networks and the TCP/IP stack
- Experience working with Linux kernel concepts or systems-level debugging tools (e.g., perf, gdb, strace, Wireshark)
- Proficiency deploying and managing workloads using Kubernetes manifests, Helm, Operators, and GitOps workflows
- Solid understanding of containerization technologies (Docker, containerd, crio) and their interaction with the Linux kernel
- Experience with observability and monitoring in distributed systems (Prometheus, Grafana, VictoriaMetrics, OpenTelemetry, or similar)
$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.
SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
xAI Palo Alto, California, USA Office
1450 Page Mill Road, Palo Alto, CA, United States
xAI San Francisco, California, USA Office
3180 18th St., San Francisco, CA, United States
Similar Jobs
Machine Learning • Payments • Security • Software • Financial Services
Lead and mature detection and incident response lifecycle, run day-to-day SOC operations, manage on‑call readiness, drive SIEM detections and automation, coordinate cross‑team responses, maintain playbooks and run readiness exercises, mentor analysts, and ensure regulatory and post‑incident improvements.
Top Skills:
Cloud SecurityEdrElasticEndpoint SecurityFedrampHipaaIdentity And Access ManagementIds/IpsIso 27035JIRAMitre Att&CkNist 800-61Pci DssServicenowSIEMSoc 2SplunkThreat Intelligence
Machine Learning • Payments • Security • Software • Financial Services
Lead and develop a team of automation engineers, own test automation backlog and frameworks, drive UI/API/performance testing, integrate AI-driven testing practices, collaborate cross-functionally, hire and mentor staff, and contribute hands-on to automation and CI/CD improvements.
Top Skills:
Agentic AiApache JmeterAWSAzureBitbucketCi/CdContainerizationCypressGCPGenerative AiGithub ActionsJavaScriptJenkinsMonitoringObservabilityPlaywrightPostmanPrompt EngineeringPythonRest ApisSeleniumTypescript
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Lead strategy, administration, and optimization of AI tools for the SDR organization (Qualified, Gong, Microsoft Co‑Pilot). Identify AI use cases, build implementation roadmaps, define requirements and success metrics, manage pilots and vendors, monitor adoption and impact, maintain governance and documentation, and partner cross-functionally to improve SDR productivity, lead conversion, and pipeline generation.
Top Skills:
6SenseAi ToolsChatbotsConversational Marketing PlatformsGongGong Agent StudioLeandataMarketoMicrosoft Co-PilotQualifiedSales Engagement PlatformsSalesforce
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
