Software Engineer - Training/Inference (C++)

SpaceXAI; Palo Alto (CA); On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical coverage

Vision coverage

Dental coverage

401(k) retirement plan

Job summary

SpaceXAI is building a high-performance inference platform used by Grok at scale. As a Member of Technical Staff - Inference, you will design and optimize distributed infrastructure for model serving, including global KV caching, batching, and auto-scaling, with deep GPU kernel work and code generation.

You will own everything from distributed infrastructure to low-level optimizations, shaping how fast and reliably users interact with Grok across millions of requests per day.

Qualifications

• BASIC QUALIFICATIONS include deep low-level systems programming in C/C++ or Rust.
• 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.
• Algorithmic inference optimizations: quantization, speculative decoding, distillation, low-precision numerics.
• Experience with testing, benchmarking, and reliability of inference services.
• Experience designing and implementing CI/CD infrastructure for inference.

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 reliable, high-concurrency serving systems that serve billions of users with high uptime, low 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.

Skills

C/C++/Rust

Large-scale serving

GPU inference engines

System optimizations

Inference optimizations

Testing & benchmarking

CI/CD for inference

Job description

Software Engineer - Training/Inference (C++)

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.

About the Role

• 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.

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 reliable, high-concurrency serving systems that serve billions of users with high uptime, low 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.

BASIC QUALIFICATIONS

• Deep low-level systems programming (C/C++ or Rust)
• Experience with large-scale, high-concurrent production serving
• Experience with GPU inference engines (vLLM, SGLang, Triton, TensorRT-LLM, etc.)
• Strong background in system optimizations: batching, caching, load balancing, parallelism
• Algorithmic inference optimizations: quantization, speculative decoding, distillation, low-precision numerics
• Experience with testing, benchmarking, and reliability of inference services
• Experience designing and implementing CI/CD infrastructure for inference

COMPENSATION AND BENEFITS

• $180,000 - $440,000 USD base salary
• Equity and comprehensive medical, vision, and dental coverage
• Access to a 401(k) retirement plan, disability and life insurance
• Other discounts and perks