Sr. Software Engineer, Training/Inference (C++)

About the role

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

SR. SOFTWARE ENGINEER, TRAINING/INFERENCE (C++)

At SpaceXSI we are building the high-performance inference platform that serves Grok to millions of users every day. As a Software Engineer, Training/Inference (C++), you will design and optimize large-scale model serving systems end-to-end. You will own everything from distributed infrastructure – global KV cache, continuous batching, load balancing, auto-scaling – to deep low-level optimizations, including GPU kernels, quantization, speculative decoding, and tail latency. This is a high-impact role where your work directly determines how fast and reliably users interact with Grok at massive scale.

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

BASIC QUALIFICATIONS:

- 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 SKILLS AND EXPERIENCE:

- 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

- Low-level inference optimizations: GPU kernels, code generation