Applied Researcher – Computer Use

🔥 16 hours ago

🏄 California – Remote

🏄 California – 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

• Build post-training and evaluation systems for multimodal agents operating browsers, desktops, and cross-application workflows. • Turn real workflows and traces into environments, rewards, and experiments that produce reliable improvement. • Build long-horizon computer-use environments from real workflows while preventing shortcuts, leakage, and unsafe side effects. • Train agents to recover from interface changes, partial failures, and ambiguous intermediate states. • Develop evaluations distinguishing genuine completion from plausible-looking behavior, including correctness, efficiency, permissions, and appropriate escalation. • Build multimodal environments from partner workflows, demonstrations, tools, interface state, and outcome criteria. • Develop browser, desktop, and cross-application agents with reliable sandbox and boundary enforcement. • Train and evaluate using demonstrations, interventions, production failures, synthetic tasks, and verifiable outcomes. • Run experiments on recovery and generalization across applications, layouts, permissions, and deployment contexts. • Work directly with customers, users, or research partners while maintaining a substantive research agenda. • Turn successful reusable work into shared research, open-source systems, and product capabilities.

🎯 Requirements

• Relevant experience: multimodal agents, computer use, browser or desktop automation, RL, imitation learning, HCI, embodied agents, or long-horizon agent evaluation. • 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 a willingness to change direction when the evidence changes. • Strong Python and the ability to build artifacts that other researchers and engineers can run, inspect, and extend. • Comfort owning ambiguous problems and keeping partners and teammates current as you resolve them. • Publications, open-source systems, benchmarks, or shipped products valued as evidence of exceptional work.

🏖️ 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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