xAI Sr. Software Engineer at SpaceXSI focusing on designing and optimizing large-scale model serving systems using C++. Responsible for distributed infrastructure and low-level optimizations including GPU kernels and quantization.
Responsibilities
Architect and implement scalable distributed infrastructure for model serving (load balancing, auto-scaling, batch scheduling, global KV cache)
Optimize latency and throughput of model inference under real production workloads
Build and operate high-concurrency serving systems with excellent tail latency and high reliability at the scale required to serve millions of users
Benchmark, fine-tune, and accelerate inference engines (including low-level GPU kernel work and code generation)
Develop custom tools to trace, replay, and fix issues across the full stack — from orchestration down to GPU kernels
Create robust CI/CD infrastructure for seamless endpoint deployment, image publishing, and inference engine updates
Accelerate research on scaling test-time compute, RL rollout, and model-hardware co-design for next-generation systems
Qualification
Bachelor’s degree in computer scienceExperience with large-scaleLow-level inference optimizationsAlgorithmic inference optimizationsExperience with testing
Required
Bachelor’s degree in computer science, computer engineering, or science discipline
5+ years of experience with low-level system programming experience in C/C++ or Rust
Preferred
Experience with large-scale, high-concurrent production serving
Experience with GPU inference engines (e.g., vLLM, SGLang, Triton, TensorRT-LLM)
Strong background in system optimizations: batching, caching, load balancing, parallelism
