Sr. Model Engineer, Mid-training
xAI is hiring a Sr. Model Engineer, Mid-training in Palo Alto, United States. It pays $180k-$440k a year and Level rates it ; you can apply on xAI.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting mentions PyTorch, JAX and fine tuning among its tools and skills.
- xAI has 307 other open roles on Level.
- Posted in the last few days.
AI in this role
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.
RESPONSIBILITIES:
- Scale synthetic coding data to trillions of tokens with large-scale docker verification
- Distill the intelligence of flagship models into flash models through synthetic data generation
- Optimize mid-training data mixtures to boost the ceiling for RL
- Engineer long-context data recipes
- Develop robust and diverse evaluation for mid-training checkpoints
BASIC QUALIFICATIONS:
- 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)
PREFERRED SKILLS AND EXPERIENCE:
- Familiarity across all kinds of scaling laws
- Strong ability to design ML experiments
- Familiarity with state-of-the-art techniques for curating AI training data for text, image, audio, and video modalities
- Strong engineering abilities in large-scale data processing frameworks
- Experience with ML and large model scaling
- Experience with Spark, Ray, and other large-scale data processing frameworks
COMPENSATION AND BENEFITS:
$180,000 - $440,000 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
Sr. Model Engineer, Mid-training 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.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Walk me through how you've used PyTorch in your day-to-day work.
- What are the limits of JAX that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- 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: Fine-tuning, 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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