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Model Engineer, Post-Training & RL

xAI is hiring a Model Engineer, Post-Training & RL in Palo Alto, United States. It pays $180k-$400k a year and Level rates it ; you can apply on xAI.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • The posting mentions PyTorch and JAX among its tools and skills.
  • xAI has 299 other open roles on Level.

AI in this role

PyTorchJAX

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.

MODEL ENGINEER, POST-TRAINING & RL

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.

RESPONSIBILITIES:

  • Design and run rigorous experiments that turn research ideas into measurable gains in model capability
  • Improve model 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

BASIC QUALIFICATIONS:

  • Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++

PREFERRED SKILLS AND EXPERIENCE:

  • 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

COMPENSATION AND BENEFITS:

$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.

SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

How we rate this

Model Engineer, Post-Training & RL at xAI rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorchJAX

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. Walk me through how you've used JAX in your day-to-day work.
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: PyTorch and JAX. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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