Sr. Software Engineer, Training/Inference (C++)
xAI is hiring a Sr. Software Engineer, Training/Inference (C++) in Palo Alto and Seattle, United States. It pays $200k-$375k a year and Level rates it ; you can apply on xAI.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 19% above the typical software engineer posting on Level.
- Tools and skills the posting cites include vLLM.
- Level lists 299 other open roles at xAI.
- The role was posted in the last few days.
AI in this 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
- 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:
$200,000 - $375,000 USD
Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
How we rate this
Sr. Software Engineer, Training/Inference (C++) at xAI rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $200k
- Typical software engineer job
- $168k
This posting starts 19% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- What's a project where you used vLLM hands-on?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: vLLM. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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