Member of Technical Staff - RL Inference
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Application is a CV plus a mandatory 'statement of exceptional work' — reviewed by engineers, not recruiters. Then a 15–30-minute phone screen with an engineer, and a main loop xAI's own job postings target to finish within ONE week: a coding assessment in your language of choice, two role-specific technical deep-dive sessions, and a 'Meet the Team' round where you present your exceptional work and your vision for xAI to a small audience. Coding is applied class design (key-value stores with transactions, LRU caches, iterators) that hardens via mid-problem extensions — completeness and bug-free code beat big-O talk — and design rounds demand working code in the same session. There is no dedicated behavioral or values round; decisions land within days with no hiring committee. Some loops run all-remote on Google Meet, others add an in-person Palo Alto onsite.
Read the full xAI interview process →Description
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:
The RL infrastructure team is looking for an engineer to help with low precision RL training and inference.
RESPONSIBILITIES:
- Design and optimize our inference stack for all shapes of RL workloads at SpaceXAI, from small scale ablations to production training runs.
- Analyze, profile and address performance bottlenecks in large scale RL systems
- Work closely with the modelling team to efficiently implement novel RL techniques and algorithms
BASIC QUALIFICATIONS:
- Experience in building, debugging, and optimizing efficiency of large-scale distributed systems
- Experience in LLM inference
- Proficiency in programming languages such as Python, C++ and/or Rust; frameworks such as PyTorch, Jax, CUDA
- Willingness to dive deep and solve hardcore problems at all levels of the stack
PREFERRED SKILLS AND EXPERIENCE:
- Strong knowledge in quantization and numerics in LLM inference and training
- Experience in developing inference engines, e.g. SGLang, vLLM
COMPENSATION AND BENEFITS:
$180,000 - $440,000 USD
Base salary is just one part of our total rewards package at SpaceXAI, 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.
SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.