We are building the high-performance inference platform that serves Grok to millions of users every day with lightning speed and perfect reliability. As a Member of Technical Staff - Inference, 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 (GPU kernels, quantization, speculative decoding, tail latency). This is a high-impact role where your work directly determines how fast and reliably users interact with Grok at massive scale.

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 reliable, high-concurrency serving systems that serve billions of users with 100% uptime, 0% error rate, and excellent tail latency.

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.