Applied Researcher – Ecosystem & Product

🔥 20 hours ago

🌐 United States, United Kingdom – Remote

🇺🇸 United States – Remote 🇬🇧 United Kingdom – Remote

🏄 California, New York – Remote

🏄 California – Remote 🗽 New York – Remote

💵 $150k - $300k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👻 Ghost score 5%

What it means: the chance that no one is really hiring for this job.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

• Turn workflows into tasks, environments, evaluations, and reward signals • Run post-training experiments against real baselines and deploy successful results • Determine whether gains come from the model, data, harness, inference, or infrastructure • Build important open-source RL, environment, evaluation, and agent systems • Shape researcher-facing features in the training platform with engineering and design • Decide which abstractions should become stable interfaces • Create APIs, examples, reference implementations, and technical explanations • Work with research users and external contributors to improve interfaces, code, and research artifacts • Help new researchers progress from environment ideas to credible evaluations and training runs • Create contributor paths for external researchers to ship environments, harnesses, algorithms, and integrations

🎯 Requirements

• Relevant experience owning open-source ML or developer-tool systems, research engineering, technical product work, or communities formed around code and reproducible research • Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops • Strong experimental judgment: meaningful baselines, careful trace inspection, clear failure attribution, and willingness to change direction when evidence changes • Strong Python skills • Ability to build artifacts that other researchers and engineers can run, inspect, and extend • Comfort owning ambiguous problems and keeping partners and teammates current • Evidence of exceptional work through publications, open-source systems, benchmarks, or shipped products

🏖️ Benefits

• Equity incentives • Flexible Work (San Francisco, New York, London, or remote) • Visa Sponsorship & relocation support • Professional Development budget • Team Off-sites & conference attendance

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