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Open nowPosted 26 days ago

【校招】强化学习算法工程师-安全基模中心

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【校招】强化学习算法工程师-安全基模中心aicarrier/522799 · Shanghai, Chinese Mainland

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This job: posted 26 days ago

The posting

1.负责大模型在AI Coding场景下的强化学习（RL）算法研发与训练，探索并落地PPO、GRPO等主流算法，提升模型在复杂代码生成、长程规划与工具调用任务中的自主推理与执行能力; 2.参与构建端到端的Agentic RL训练链路，结合过程奖励机制（Process Reward）与Critic Model，优化Agent在真实环境中的行为引导、指令跟随与自我反思能力; 3.负责AI Coding相关高质量RL训练数据的挖掘、合成与评测体系设计，针对模型能力短板构建可验证的训练闭环，持续提升模型在前沿Benchmark及真实业务场景中的表现; 4.与算法、Infra团队紧密协作，参与RL训练系统的性能优化与工程化落地，解决训推分离场景下的大规模训练稳定性、吞吐瓶颈及长尾任务问题。

1.计算机、人工智能、软件工程等相关专业本科及以上学历，具备2年以上大模型强化学习或AI Agent相关研发经验。 2.具备扎实的强化学习基础，深入理解PPO、GRPO等算法原理，有实际跑通并优化过RL训练Pipeline的完整经验。 3.在AI Coding、代码基座模型或Agentic RL方向有实际项目落地经验，熟悉代码生成、自动修复、测试框架等场景的RL训练方法。 4.具备出色的代码能力与工程素养，熟练掌握Python，熟悉C++/Go/Rust中至少一种系统级语言，具备良好的代码规范与问题定位能力。 5.对模型行为有较强洞察力，能够结合实际问题独立分析失败案例，设计Reward信号并持续迭代训练方案。 加分项 具备强化学习Infra或分布式训练系统背景，熟悉Ray、DeepSpeed、Megatron-LM、vLLM等框架，有大规模RL训练平台的开发或优化经验者优先。 有开源项目贡献经历，或在ACM/ICPC、Kaggle等知名竞赛中取得优异成绩。 熟悉Code Harness、Runtime环境构建，或有过Long Horizon Task相关的训练与评测经验。 具备顶会论文发表或知名开源项目贡献经历，能够沉淀并分享具有行业影响力的技术成果。

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