Sr. Model Engineer, Post-Training & RL

5 дн. назад

СШАSenior

pythonpytorchjaxrustc++

Senior AI Engineer working on post-training and reinforcement learning challenges including reward modeling and preference optimization.

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)

You believe truth-seeking AI is the most important and challenging problem
You are obsessed about building incredibly useful models through post-training and RL techniques
You are a power user of AI models and eager to push the boundaries of what’s possible with reinforcement learning and alignment methods
If you previously worked on post-training, RLHF, or trained models used by millions of people it’s a big plus, but relevant experience is not required
You take pride in your work and thrive in meritocratic environments

$180,000 - $600,000 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.
You will work on the most critical post-training and reinforcement learning challenges at any given time — including reward modeling, preference optimization (RLHF/DPO), and RL for improving reasoning, truthfulness, and real-world capabilities.