Applied Research – Robotics

🔥 15 hours ago

🌐 United States, United Kingdom – Remote

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

🏄 California – Remote

🏄 California – Remote

💵 $150k - $300k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Robotics

👻 Ghost score 3%

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 environments, evaluations, agent systems, and post-training methods with an external robotics team • Train and evaluate agents using reinforcement learning, world modeling, imitation learning, planning, and multimodal perception • Use feedback from simulation and deployed robots • Test behavior under partial observations, long horizons, changing environments, and hardware and safety constraints • Build aligned simulation and real-world evaluations for long-horizon embodied tasks • Combine demonstrations, interventions, offline data, and online feedback into training loops • Train embodied agents to recover from partial failures, changing scenes, and uncertain states • Own simulation and real-world environments for training, evaluation, and sim-to-real comparison • Own long-horizon agents that perceive, plan, act, remember, and recover under hardware constraints • Develop rewards and evaluations for task success, safety, adaptation, and continual improvement • Work directly with customers, users, or research partners while maintaining a substantive research agenda

🎯 Requirements

• Relevant experience in robotics, embodied AI, RL, imitation learning, control, world models, simulation, computer vision, agent evaluation, or production systems interacting with the physical world • 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 • 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