Grafton Sciences
Senior LLM Research Scientist
Grafton Sciences, Redwood City, California, United States, 94061
About Grafton Sciences
We’re building AI systems with general physical ability — the capacity to experiment, engineer, or manufacture anything. We believe achieving this is a key step towards building superintelligence. With deep technical roots and real-world progress at scale (e.g., a $42M NIH project), we’re pushing the frontier of physical AI. Joining us means inventing from first principles, owning real systems end-to-end, and helping build a capability the world has never had before. About The Role
We’re seeking a Senior LLM Research Scientist to develop advanced planning, reasoning, and tool-use models that drive autonomous engineering systems. You’ll lead work in prompting frameworks, structured tool calling, model alignment, preference optimization, verifier-guided RL, and long-horizon planning. This role spans fundamental research, systems integration, and hands‑on experimentation with agents interacting with real engineering toolchains. Responsibilities
Develop models and prompting frameworks for planning, tool use, and long‑horizon reasoning. Lead SFT, RLHF/DPO, verifier‑driven RL, and MoE routing strategies for robust agent behavior. Design schemas, tool‑call policies, safety constraints, and failure‑recovery mechanisms for LLM agents. Collaborate with agent systems, data infrastructure, simulation, and tooling teams to train and evaluate models in real workflows. Qualifications
Deep experience in LLM research, reasoning models, agent systems, or structured tool‑use frameworks. Strong background in SFT, RLHF, DPO, or verifier‑driven RL, with a track record of pushing model capabilities. Ability to design and evaluate long‑horizon behaviors, decomposition strategies, and structured policy constraints. Comfortable working across ML, systems engineering, and real‑world toolchains in a fast‑moving research environment. Above all, we look for candidates who can demonstrate world‑class excellence. Compensation
We offer competitive salary, meaningful equity, and benefits. Seniority level
Mid‑Senior level Employment type
Full‑time Job function
Other
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We’re building AI systems with general physical ability — the capacity to experiment, engineer, or manufacture anything. We believe achieving this is a key step towards building superintelligence. With deep technical roots and real-world progress at scale (e.g., a $42M NIH project), we’re pushing the frontier of physical AI. Joining us means inventing from first principles, owning real systems end-to-end, and helping build a capability the world has never had before. About The Role
We’re seeking a Senior LLM Research Scientist to develop advanced planning, reasoning, and tool-use models that drive autonomous engineering systems. You’ll lead work in prompting frameworks, structured tool calling, model alignment, preference optimization, verifier-guided RL, and long-horizon planning. This role spans fundamental research, systems integration, and hands‑on experimentation with agents interacting with real engineering toolchains. Responsibilities
Develop models and prompting frameworks for planning, tool use, and long‑horizon reasoning. Lead SFT, RLHF/DPO, verifier‑driven RL, and MoE routing strategies for robust agent behavior. Design schemas, tool‑call policies, safety constraints, and failure‑recovery mechanisms for LLM agents. Collaborate with agent systems, data infrastructure, simulation, and tooling teams to train and evaluate models in real workflows. Qualifications
Deep experience in LLM research, reasoning models, agent systems, or structured tool‑use frameworks. Strong background in SFT, RLHF, DPO, or verifier‑driven RL, with a track record of pushing model capabilities. Ability to design and evaluate long‑horizon behaviors, decomposition strategies, and structured policy constraints. Comfortable working across ML, systems engineering, and real‑world toolchains in a fast‑moving research environment. Above all, we look for candidates who can demonstrate world‑class excellence. Compensation
We offer competitive salary, meaningful equity, and benefits. Seniority level
Mid‑Senior level Employment type
Full‑time Job function
Other
#J-18808-Ljbffr