AI Research Engineer (Agentic Post-training) - 100% Remote Worldwide

As a member of the AI model team, you will drive innovation in post-training methodologies, with a special focus on agentic behaviors and tool use.

Your work will refine pre-trained models so that they not only deliver enhanced intelligence and domain specific capabilities, but also learn to reason, plan, and autonomously invoke external tools to solve real world, multi step tasks and applications on edge devices (i.e., smartphones).

You will work on a wide spectrum of systems, ranging from streamlined, resource efficient agents that run on limited hardware to complex multi modal architectures integrating text, images, and audio, all optimized for tool augmented decision making.

We expect you to have deep expertise in large language model architectures and substantial experience in post-training for agentic workflows, including tool use fine tuning, function calling, and reinforcement learning from feedback on multi turn interactions.

You will adopt a hands-on, research driven approach to developing, testing, and implementing new post-training algorithms that unlock goal directed behavior, self correction, and reliable tool invocation.

Your responsibilities include curating agentic training data (e.g., trajectories of tool use, reasoning chains, environment interactions), strengthening baseline performance, and identifying as well as resolving bottlenecks in post-training for tool augmented agents to achieve SOTA model quality.

The goal is to build models that do not just know but also act, use tools, and adapt, pushing the limits of what agentic AI can achieve.