Sr. Model Engineer, Mid-training

X.ai; Palo Alto (CA); On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical insurance

Vision insurance

Dental coverage

401(k) retirement plan

Disability insurance

Life insurance

Discounts and perks

Job summary

SpaceXSI is seeking a machine learning engineer to scale synthetic data for trillions of tokens, distill flagship models into efficient flash models, and optimize data mixtures for RL training.

You will design ML experiments, work with PyTorch/JAX/C++, Spark and Ray on large-scale data pipelines, and contribute to a world-class AI research stack.

Qualifications

• Production-quality coding in Python, PyTorch, JAX, Rust, or C++.
• Experience training large models (1B+ parameters).
• Familiarity with ML experiments design and scaling laws.

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.

Skills

Production-grade code

Large model training

Tools

Spark

Ray

Large-scale data frameworks

Job description

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.