Autonomous Research Scientist, Frontier AI & Tools

Prime Intellect AI; San Francisco (CA); A distancia; USD 150.000 - 300.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Cash compensation + equity incentives

Flexible work locations (SF, NYC, LDN,

Visa sponsorship & relocation support

Professional development budget

Team off-sites & conference attendance

Descripción de la vacante

Prime Intellect AI in San Francisco and beyond is seeking researchers to build and post-train agents for autonomous scientific exploration. You will operate at the intersection of frontier research and infrastructure, shaping tools, data, and feedback loops for real-world partnerships.

Responsibilities span RL/multi-agent methods, reproducible experiments, and collaboration with customers and researchers to drive credible, verifiable advances in frontier AI.

Formación

• Depth in RL, agents, or post-training systems.
• Autonomous research, ML for science, or reproducible computational research is useful.
• Hands-on experience building and debugging model-training, post-training, agent, evaluation loops.

Responsabilidades

• 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.

Conocimientos

Reinforcement Learning

Agent development

Autonomous research

Experiment loops

Python proficiency

Ambiguity handling

Descripción del empleo

Prime Intellect AI in San Francisco and beyond is seeking researchers to build and post-train agents for autonomous scientific exploration. You will operate at the intersection of frontier research and infrastructure, shaping tools, data, and feedback loops for real-world partnerships.

Responsibilities span RL/multi-agent methods, reproducible experiments, and collaboration with customers and researchers to drive credible, verifiable advances in frontier AI.