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.