en.Wedoany.com Reported - China's artificial intelligence company DeepSeek released a recruitment announcement on June 25, stating that as technology continues to evolve, the company is striving to at least double the size of all departments. This recruitment covers multiple areas including full-stack development, algorithms, AI core system R&D, operations, product design, model data strategy, deep learning research, and functional positions, spanning basic R&D, engineering systems, product implementation, and organizational support.
The recruitment announcement shows that this expansion by China's DeepSeek is not merely filling vacancies in a single position, but rather simultaneously expanding team sizes across multiple business departments. Job categories include full-stack development/algorithms, AI core system R&D, operations, product design, model data strategy product managers/engineers, deep learning research, and functional positions. Some technical roles also involve the Agent Harness team and Agent Infra R&D engineer positions, indicating that beyond model capabilities, the company continues to strengthen agent engineering, infrastructure, and productization capabilities.
In its hiring philosophy, China's DeepSeek emphasizes that new hires will directly undertake core, cutting-edge tasks. The company states that humanity is currently on the eve of AGI, and joining DeepSeek means experiencing technological change firsthand, standing at the forefront of the era, and witnessing the dawn of a new epoch. While this phrasing is part of recruitment communication, it also reflects the company's desire to attract algorithm, engineering, product, and research talent into its core business chain through more aggressive job openings.
The full-stack development and algorithm positions involved in this recruitment primarily correspond to the needs for model products, engineering platforms, and application system development. AI core system R&D and operations positions are closer to model training, inference services, computing power scheduling, system stability, and infrastructure assurance. Model data strategy-related positions typically handle data organization, evaluation systems, model iteration, and product feedback integration tasks. Deep learning research positions directly serve model capability enhancement, algorithm exploration, and technical route iteration.
The emergence of Agent Harness and Agent Infra positions makes this recruitment more targeted. Agent Harness is usually related to agent operation frameworks, tool invocation, task orchestration, interaction chains, and effect evaluation; Agent Infra leans more towards agent underlying infrastructure, service stability, engineering frameworks, and large-scale deployment capabilities. As large models move from single-turn Q&A to complex task execution, agent-related positions are becoming an important component in the expansion of large model companies.
China's DeepSeek previously attracted attention in the AI industry due to its large model products. With the simultaneous advancement of model R&D, agent systems, computing power infrastructure, product experience, and commercial implementation, the company's demand for composite talent has significantly increased. The proposal to at least double all department sizes means the company's expansion focus is not limited to research teams, but also covers engineering, operations, products, data, and functional support. For large model companies, model capability is just the foundation; stable delivery, continuous iteration, and product implementation equally rely on organizational scale and engineering capability.
The recruitment announcement did not disclose the current total number of employees, existing sizes of each department, planned number of new hires, recruitment cycle, or salary range. What is clear is that China's DeepSeek is initiating a broad organizational expansion, with recruitment directions concentrated on AI R&D, core systems, model data, agent engineering, product design, and functional support. The subsequent effectiveness of the expansion will depend on the speed of position filling, team collaboration capabilities, model iteration pace, and the progress of agent product development.
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