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Location
In office (Beijing)
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Jun 1, 2026. Li Auto scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Li Auto manufactures electric vehicles including extended range and battery electric models. Its cars emphasise family-oriented cabins with large screens and voice assistants. The company develops its own driver assistance software and computing platform.

岗位职责 / Responsibilities

1. 建设 AI 平台 MLOps 能力,覆盖训练、评测、推理、数据全流程流水线。

2. 设计并落地模型研发流水线:任务编排、参数与产物管理、评测联动、发布、可观测。

3. 基于 K8s、Workflow、调度系统,构建可扩展、可复用的平台能力,提升研发效率与资源利用率。

4. 推动 Agent 工程化方向,参与 OpenClaw / Claude Code / Agent CLI 等工具链在研发与运维流程的落地。

5. 沉淀最佳实践,推动训练、评测、推理场景从人工走向自动化、智能化。

任职要求 / Requirements

1. 本科及以上,计算机相关专业。

2. 3 年以上后端 / 平台 / MLOps / AI Infra 经验。

3. 熟悉 Python 或 Go,工程设计与问题排查能力扎实。

4. 熟悉 K8s、容器、Workflow、任务调度。

5. 理解模型研发流程(训练、评测、管理、发布)。

6. 具备平台化思维,能将复杂流程抽象为标准化、自动化能力。

7. 对 Agent、Claude Code、Cursor、MCP、工具调用等方向有了解或实践。

加分项

- Kubeflow、Argo Workflow、Ray、Volcano 等平台或组件经验。

- 大模型训练 / 推理平台、GPU 集群调度、模型评测平台建设经验。

- Agent 工具链、智能工单、研发助手等落地经验。

- 复杂流程平台化、跨团队推动方案落地经验。

岗位亮点

1. 深度参与公司级 AI 平台建设,覆盖训练、评测、推理、数据与 Agent 工程化全链路。

2. 面向真实大规模 AI 场景,解决效率、稳定性、资源治理和自动化问题。

3. 参与 AI Infra 向 Agent Native 平台演进,推动研发流程从"人操作平台"升级为"Agent 驱动任务"。

4. 技术挑战大、场景复杂,适合长期深耕 AI Infra / MLOps 方向的工程师。

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