AI Large Model Algorithm Engineer (Mental and Psychological Health)

Job Responsibilities

1. Participate in Building the Agent’s Memory Center: In-depth research and lead the design of the Agent’s long-term and short-term memory systems. You will be responsible for building dynamic, evolving user profiles and knowledge bases, solving the “amnesia” pain point of large models in long-cycle services, enabling the Agent to remember users, understand the context, and provide truly coherent and personalized services.

2. Participate in Decision-Making Chain Optimization: Participate in the technical upgrade and performance optimization of the Agent’s core decision-making chain (task planning, reasoning, tool invocation). Ensure that complex business strategies can be executed accurately and efficiently by the Agent, and be responsible for key performance indicators such as task success rate and response time.

3. Participate in Building Memory Acquisition Mechanisms Based on Various Retrieval Strategies: Build agent strategies for memory acquisition mechanisms based on keywords, Embeddings, and parameterized memory models.

Job Requirements

1. Master’s degree or above in Computer Science, Artificial Intelligence, or a related field, with a solid foundation in Python programming and algorithms.

2. Experience in Agent development, a deep understanding of LLM principles, familiarity with technologies such as RAG and Prompt Engineering, and the ability to skillfully use frameworks such as LangChain and LlamaIndex.

3. Excellent logical thinking and problem-solving skills, good at data-driven decision-making, responsible for the final business results, and willing to accept challenges.

4. Mastery of ES/vector databases/retrieval and ranking strategies is preferred, advanced RAG and Search RL experience is preferred.