Research Engineer - Pre-training

• Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
• Build and extend the pre-training code in prime-rl, taking small experiments into full training runs.
• Evaluate model architecture changes, including MoE and attention designs, against model quality and training cost.
• Profile training jobs and improve end-to-end throughput, working with systems engineers on hardware-aware execution.
• Make long runs resilient to failures, with reliable checkpointing and recovery.
• Investigate training dynamics and numerical stability, checking that optimizations preserve convergence.
• Run controlled ablations to guide larger experiments, keeping the setup and results reproducible.
• Work with data and evaluation researchers on training mixtures, including midtraining and long-context experiments.
• Hands-on experience training language models, including modifying training code and following the effects through actual runs.
• Strong Python skills and experience with PyTorch or a comparable framework, with enough systems understanding to debug distributed training.
• A practical understanding of model architectures and optimization, including their effect on convergence.
• Ability to design an ablation that answers a research question and explain what its results do and don’t show.
• Good judgment about what to investigate yourself and when to bring in a colleague.

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