About the role
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.
RESPONSIBILITIES: 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. BASIC
QUALIFICATIONS: 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 PREFERRED SKILLS AND EXPERIENCE: 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)