Autonomous Research AI Scientist — RL & Agents (Remote)

Prime Intellect, Inc.; United States; À distance; USD 150 000 - 300 000; Plein temps

Avantages offerts par ce poste

Cash compensation $150k–$300k + equity

Flexible work locations (SF, NYC, LON,

Visa sponsorship & relocation support

Professional development budget

Résumé du poste

Prime Intellect, Inc. is building an open frontier AI stack to enable research teams to turn workflows, tools, and data into scalable, post-training intelligence.

You will develop post-training agents for autonomous scientific tasks, collaborating with research partners to push the boundaries of frontier AI. The role emphasizes designing experiments, evaluating hypotheses, and ensuring reproducible results across diverse environments and datasets.

Responsabilités

• Build long-horizon environments where agents search literature, query scientific databases, run code and domain tools, and choose experiments within a fixed compute or experimental budget.
• Turn research partners' workflows, datasets, and outcome criteria into trainable tasks, evaluations, and reward signals.
• Design verifiers for correctness, novelty, and reproducibility. Test whether agents use the underlying evidence, with checks for label leakage, lookup shortcuts, and unsupported conclusions.
• Connect programmatic checks, simulations, domain models, and expert feedback to training. Account for noisy or delayed results, calibrate confidence estimates, and define where an experiment needs human review.
• Develop RL and multi-agent methods for proposing, testing, and critiquing hypotheses. Compare them with strong single-agent baselines at equal compute and evaluate on held-out problems.
• Keep code, data, logs, and experiment configurations reproducible. Re-run promising results, measure noise, and use ablations to separate model improvements from changes to the data, harness, or inference setup. Release reusable environments, evaluations, and research code.

Description du poste

Prime Intellect, Inc. is building an open frontier AI stack to enable research teams to turn workflows, tools, and data into scalable, post-training intelligence.

You will develop post-training agents for autonomous scientific tasks, collaborating with research partners to push the boundaries of frontier AI. The role emphasizes designing experiments, evaluating hypotheses, and ensuring reproducible results across diverse environments and datasets.