Sr. Model Engineer, RL Training Framework

3 дн. назад

СШАSenior

pythonpytorchjaxrustc++

Engineer to develop and optimize reinforcement learning training framework at .

Design and implement the systems backing all RL workloads at SpaceXSI, from small scale ablations to production training runs
Profile, debug, and optimize end-to-end training performance
Improve scalability and observability of the RL stack

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 building, debugging, and optimizing efficiency of large-scale distributed systems
Experience with large scale LLM training infrastructure
Experience with RL numerics
Strong knowledge of reinforcement learning techniques
Comfortable diving into unfamiliar areas and solving problems at all levels of the stack

$180,000 - $400,000 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.

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.
The RL infrastructure team is looking for an engineer to help develop our RL training framework.