Description:

Build core agent behavior for a revenue-focused AI agent, from harness and evaluations to fine-tuning and reinforcement learning.
Own and advance the agent harness, improving tool selection, context building, and multi-step task handling through experimentation.

Requirements:

5+ years of experience in applied AI research or applied science at a senior level.
MS or PhD in Computer Science, Mathematics, Statistics, or a related quantitative discipline.
Hands-on experience with agentic systems, LLMs, and large-scale deep learning systems.
Proven ability to scope and drive ambiguous research with minimal guidance.
Publications in top-tier peer-reviewed conferences or journals preferred.

Skills