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Posted 9 months ago

Open

Research Scientist

San FranciscoOn-siteFull-time

AI Summary

Design and implement novel architectures for automated research, collaborating with researchers on long-horizon agentic capabilities and environment development.

About this role

Overview

Join our core R&D team building end-to-end automated research systems.

馃摪 Zochi publishes the first fully-AI generated A* conference paper

馃摪 Locus becomes the first AI-system to outperform human experts at AI R&D

Key Responsibilities

  • Design & implement novel architectures for automated research.

  • Collaborate with a focused group of researchers tackling problems at the forefront of long-horizon agentic capabilities, post-training for open-ended goals, and environment development.

  • Publish internal key-findings along with external collaboration success stories.

Qualifications

  • PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree.

  • Proven track-record of high-impact AI/ML research contributions in either the academic or corporate settings.

  • Expertise in developing long horizon. multi-agent systems and/or model post-training, with a focus on capabilities. Even better if built for scientific domains and/or open-ended discovery purposes.

  • Passion for accelerating the process of problem-solving & scientific discovery, with comfort in high-autonomy roles & environments.

Our Culture

  • Competitive salary & equity packages.

  • Unlimited PTO with a focus on on-site team-building & communal work environment.

  • Conference attendance & involvement in community-facing events.

  • High-agency & responsibility.

#1: We are are small, dedicated group of top investors, researchers, and industry veterans, dedicated to the mission of accelerating discovery. Join us.

Skills

Artificial IntelligenceEnvironment DevelopmentLong-horizon PlanningMachine LearningModel Post-trainingMulti-agent SystemsReinforcement LearningResearch Scripting

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