XA
xAISr. Model Engineer, RL Inference
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Before you apply
Salary$180k – $440k
LocationPalo Alto, CA, Palo Alto, CA
Work modeon-site
Typefull-time
SenioritySenior
DepartmentModel
EquityIncluded
Company size1,001–5,000 people
PostedJul 6, 2026 · 4mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++
Experience training large models (e.g., pre-training, post-training, fine-tuning, or RL training of neural networks with 1B+ parameters)
Experience in building, debugging, and optimizing efficiency of large-scale distributed systems
Experience in LLM inference
Strong knowledge in quantization and numerics in LLM inference and training
Experience in developing inference engines, e.g. SGLang, vLLM
Willingness to dive deep and solve hardcore problems at all levels of the stack
Skills
Python
PyTorch
JAX
Rust
C++
SGLang
vLLM
Benefits
Equity
Medical coverage
Vision coverage
Dental coverage
401(k)
Short term disability insurance
Long term disability insurance
Life insurance
About the company
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. MODEL ENGINEER, RL INFERENCE
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 SpaceXSI, from small scale ablations to production training runs
•
Analyze, profile and address performance bottlenecks in large scale RL systems
•
Work closely with the modeling team to efficiently implement novel RL techniques and algorithms
BASIC QUALIFICATIONS:
•
Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++
•
Experience training large models (e.g., pre-training, post-training, fine-tuning, or RL training of neural networks with 1B+ parameters)
PREFERRED SKILLS AND EXPERIENCE:
•
Experience in building, debugging, and optimizing efficiency of large-scale distributed systems
•
Experience in LLM inference
•
Strong knowledge in quantization and numerics in LLM inference and training
•
Experience in developing inference engines, e.g. SGLang, vLLM
•
Willingness to dive deep and solve hardcore problems at all levels of the stack
COMPENSATION AND BENEFITS:
$180,000 - $440,000 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.
Legal
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.