Research Engineer – Pretraining

Job not on LinkedIn

🔥 18 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $150k - $350k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📚 Research Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Prime Intellect

WebsiteLinkedInAll Job Openings

1 - 10 employees

🤖 Artificial Intelligence

☁️ SaaS

Artificial Intelligence • SaaS • Cloud Computing

Prime Intellect is a company focused on democratizing AI development by providing scalable and decentralized computing resources for training models. Their platform allows users to find and share global compute resources, enabling the training of state-of-the-art models through distributed clusters. They promote the collective ownership of AI innovations, including language and scientific models. Prime Intellect also offers a range of GPU options to facilitate affordable and efficient model training. They aim to advance decentralized training research and open-source AI development on a global scale.

📋 Description

• Build and extend the pretraining 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 with systems engineers on hardware-aware execution • Make long runs resilient to failures through reliable checkpointing and recovery • Investigate training dynamics and numerical stability, ensuring optimizations preserve convergence • Run controlled ablations to guide larger experiments while keeping setup and results reproducible • Work with data and evaluation researchers on training mixtures, including midtraining and long-context experiments • Take the next open models from architecture experiments through full pretraining runs, scaling toward 1–3T parameters

🎯 Requirements

• Hands-on experience training language models, including modifying training code and following the effects through actual runs • Strong Python skills • Experience with PyTorch or a comparable framework • Systems understanding sufficient to debug distributed training • Practical understanding of model architectures and optimization, including their effect on convergence • Ability to design ablations that answer research questions and explain what results do and do not show • Good judgment about what to investigate independently and when to involve a colleague

🏖️ Benefits

• Equity incentives included in cash compensation range • Flexible work arrangements, with the option to work remotely or in-person at offices in San Francisco • Visa sponsorship • Relocation assistance for international candidates • Quarterly team off-sites • Hackathons • Conferences and learning opportunities • Opportunity to work with a talented, hard-working and mission-driven team