Sr. Model Engineer

вчера

СШАSeniorOnsite

reinforcement learningmachine learningexperiment designdata qualitymodel training

Research scientist role focused on reinforcement learning and model training research to improve AI model capabilities.

Design and run rigorous experiments that turn research ideas into measurable gains in model capability
Improve data recipes through data quality, deduplication, and mixture experiments
Define what makes RL data and rewards good, including grader design and preventing reward hacking
Advance training science, from architecture and scaling experiments to post-training recipes for coding and computer-use agents
Build evals and targeted tasks that expose model weaknesses and guide where the team invests next
Partner with engineers to take promising results from small experiments to frontier-scale training runs

3+ years of hands-on experience training or post-training large neural networks (1B+ parameters), including work on pre-training, fine-tuning, or RL-based methods (e.g., RLHF, DPO).
Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++
Onsite role: must be able to work in person at the Palo Alto office

Able to handle ambiguous research tasks with little guidance, and to own a research direction end to end
Care an unusual amount about data quality, and can dive into the data when appropriate
Truth seeking, aiming to learn more about the science than to prove your ideas are correct
Experience with RL algorithms for language models, scaling laws, or building RL environments and evals
Experience with distributed training at scale and debugging problems that only show up at scale
Experience training frontier-scale models
Strong background in RL and machine learning fundamentals
An excellent programmer and software engineer, comfortable working across the research stack in Python and PyTorch or JAX
Hands-on experience training large models, through pretraining, post-training or RL
A track record of original work in ML, such as new methods or real improvements, shown through research, open source or production impact
MS or PhD in CS, ML, math, physics or a related field, or equivalent research experience

The annual compensation range for this role is listed below.
$220,000 - $357,000 USD
Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.
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.
SpaceXSI is building Super Intelligence to help humanity understand the universe. We train frontier coding agents and scale RL on real user data to make them increasingly effective. We're looking for Research Scientists who can drive effective RL or mid-training research in a small-team setting. You'll own ambiguous, hard research problems end-to-end: forming hypotheses, designing experiments, building the training/eval/data needed to test them, and pushing results into the next model.