Research Scientist, Frontier Capabilities

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About this role

Research Scientist, Frontier Capabilities Cambridge, MA USA; San Francisco, CA USA Your impact at LILA We're building a talent-dense, high-agency research team to develop the next generation of learning systems and reasoning algorithms for agentic LLMs. Our work sits at the intersection of large language models, post-training, and scientific reasoning, with the goal of enabling systems that learn from experience, reason effectively, and improve through interaction . Scientific domains present a distinct set of challenges that make this problem uniquely hard. Feedback is sparse and delayed - experiments take days or weeks, not milliseconds. Ground truth is expensive or contested. Distribution shift is structural, as instruments, techniques, and knowledge bases evolve continuously. The hypothesis space is vast and reward signal is thin. Existing benchmark do not capture these nuances. The goal is to build systems that can operate effectively in this scientific regime. This role spans a few complementary directions. Candidates are expected to bring deep expertise in one (ore more) of the following areas. In the event of cross-track expertise, please select the one you align to the most. Our interview process will be catered to verifying the chosen expertise area. Expertise Area 1 - Agentic system building Focus: Build systems that autonomously propose, execute, and verify scientific hypotheses over long time horizons. - Create and analyze long-running auto-research systems that propose and verify hypotheses - Design planning frameworks for agentic systems operating over long, sparse feedback loops - Design memory architectures that allow agents to build and retrieve

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