Build and optimize the RL training framework and infrastructure for large-scale workloads at SpaceXAI, from ablations to production runs. Requires experience with distributed systems and proficiency in Python, JAX, Rust, or C++.
180k – 440k
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About the role
Responsibilities
Design and implement the systems backing all RL workloads at SpaceXAI, 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.
Basic Qualifications
Experience building, debugging, and optimizing efficiency of large-scale distributed systems.
Comfortable diving into unfamiliar areas and solving problems at all levels of the stack.
Proficiency in Python, Jax, Rust, and/or C++.
Preferred Skills and Experience
Experience with large scale LLM training infrastructure.
Strong knowledge of reinforcement learning techniques.
Experience with RL numerics.
Compensation and Benefits
$180,000 - $440,000 USD total compensation (base salary is one part of total rewards, which also includes equity and benefits).
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