According to 1M AI News monitoring, DeepSeek has opened 17 job positions, with a core research focus shifting from foundational model research to Agent productization. Three dedicated Agent roles cover algorithm research, data evaluation, and infrastructure across the entire chain: Algorithm researchers focus on applying reinforcement learning to large model alignment (RLHF/RLAIF, reward shaping, preference learning, etc.); data evaluation experts are responsible for building evaluation datasets and designing test cases for Agent capabilities such as planning, tool invocation, multi-turn interactions, and long-term memory; infrastructure engineers are tasked with building the Agent runtime platform, including integrating external tools into internal reinforcement learning infrastructure and setting up evaluation platforms.
Two notable signals stand out in the job requirements. Multiple positions explicitly prioritize candidates who are “heavy users of AI programming tools such as Claude Code, Cursor, Copilot, etc.” The full-stack developer role includes an uncommon description: “As a heavy user of Vibe Coding, continuously exploring innovative applications of model capabilities in products,” with the core responsibility of building “the next-generation container scheduling and isolation platform to support the operation of massive AI Agents.”
The Model Strategy Product Manager role is specifically focused on the Agent direction, requiring candidates to be familiar with Agent products like Claude Code, OpenClaw, Manus, etc., and to have insights into high-value application scenarios (including personal assistants, Deep Research, automation workflows, multi-modal device control). They are also expected to lead the design of Agent evaluation systems and training data schemes. Compared to January of this year, when core positions focused on general directions like “Deep Learning Researcher - AGI,” this recruitment shift clearly leans toward Agent productization.