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Location
In office (Beijing)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Sep 16, 2026.

Overview
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Profile match
点击进入 关于我们 2015 成立时间(年) 650+ 管理规模(亿元) 15+ 核心人员从业年限(年) 100% 投研团队均为清北等国内外知名高校硕博及以上 宁波平方和投资管理合伙企业(有限合伙)成立于2015年8月,是经中国证券投资基金业协会备案的量化对冲基金公司,总部位于北京。 秉持"以投研为本,追求卓越"的核心价值观,平方和综合利用大数据及算法技术,挖掘市场深层规律,构造数量化的对冲基金策略模型,力求在不同市场周期下能为投资者带来长期稳健的策略表现。 截至2026年9月,平方和资产管理规模超过650亿元人民币,多次荣获中国私募界权威荣誉金牛奖。 发展历程 2015 崭露头角…

岗位职责:

1、持续迭代与优化强化学习算法,在预训练模型与数据既定的条件下,最大限度地释放模型潜力。

2、与跨部门团队紧密协作,构建高质量、高多样性的后训练数据集; 设计并落地自动化的数据清洗、评测与合成管线,系统性提升模型在写作、问答、Agent 等核心场景的表现。

3、建立科学、敏捷、多维度的模型能力评测体系,覆盖通用能力与 Agent 场景,精准定位模型短板并驱动针对性优化。

岗位要求:

1、对大模型后训练有深入理解,熟悉 RLHF / RLVR / PPO / GRPO 等主流强化学习框架与范式,具备从算法设计到工程落地的完整经验。

2、具备扎实的数据直觉与工程能力,能够从复杂、多源的数据中提炼信号,并将数据清洗、筛选与合成流程系统化、自动化。

3、对模型评测有方法论层面的思考,不满足于"刷 benchmark",而是能设计出真正反映模型能力边界与短板的评测方案。

加分项:

1、熟悉 PyTorch 等深度学习框架,具备大规模训练、分布式训练或推理加速的实战经验。

2、熟悉 SFT、DPO、奖励模型、偏好数据构建等后训练相关技术栈。

3、在大模型、强化学习或相关方向有顶会/顶刊论文,或有开源模型、数据集、训练框架的贡献。

4、ACM/ICPC/NOIP/NOI 等赛事获奖选手。

5、对 Agent、工具调用、长程任务等前沿方向有研究或实践经验。

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