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.