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Open nowPosted 2 days ago

AI Platform Engineer

cat920 open roles

Where
Wuxi Jiangsu
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Your applicationOpen nowAI Platform Engineercat · Wuxi Jiangsu

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The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. cat postings stay open a median of 13 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted 2 days ago

cat median: 13 days open

The posting

Career Area:

Technology, Digital and Data

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

AI 平台工程师

AI Platform Engineer

岗位概述

负责建设和运营可扩展的 AI 数据、训练、评估与 MLOps 基础设施，支持感知、预测、VLA、调度优化等团队高效开发、验证和管理 AI 模型，并确保数据、模型、配置和评估结果能够复用、追溯和持续演进。

岗位职责

• 数据平台建设：建设自动驾驶车端和矿山现场数据的采集、接入、处理与存储能力，支持传感器数据、车辆状态、动作、运营数据及仿真数据的统一管理。

• 数据集与标注管理：建立数据集版本、元数据、标注流程和数据质量机制，支持 Corner Case、Failure Case、Demonstration Data 及多模态 Vision-Language-Action 数据管理。

• 训练与评估平台：建设可复用的训练任务、算力调度、实验追踪和自动评估能力，支持传统 ML、深度学习、VLM / VLA 及后台优化模型的开发。

• MLOps 与模型生命周期：建设 Model Registry、Artifact 管理和模型生命周期流程，维护代码、数据、配置、Checkpoint、模型及评估结果之间的可追溯关系。

• 交付基础设施：提供模型打包、候选版本管理、Deployment Pipeline Infrastructure 和回滚机制；模型是否发布以及发布范围由相应 On-board 或 Back-office 产品团队负责。

• 平台可靠性与效率：持续提升数据与训练 Pipeline 的稳定性、可扩展性、资源利用率和开发者体验，并建立必要的监控、告警和问题诊断能力。

• 跨团队协作：与感知、预测、规划、VLA、调度优化、AI Runtime、Validation、Cybersecurity 和 Functional Safety 团队协作，将共性需求沉淀为标准化平台能力。

任职要求

• 计算机、人工智能、软件工程、数据工程、自动化或相关专业硕士及以上学历。

• 5-8 年软件、数据平台、机器学习平台或 MLOps 相关研发经验，能够独立负责关键平台模块的设计和交付。

• 熟练使用 Python，具备良好的软件工程能力，熟悉至少一种主流机器学习框架，如 PyTorch 或 TensorFlow。

• 熟悉数据处理、分布式训练、实验追踪、Model Registry、模型评估和 CI/CD 等机器学习生命周期能力。

• 熟悉 Kubernetes、Docker、MLflow、Ray、Airflow、Kubeflow、SageMaker 或同类平台中的一种或多种。

• 理解数据与模型版本、Lineage、可重复训练、Deployment Pipeline 和生产环境监控的工程要求。

• 具备良好的跨团队沟通、问题分析和英文技术交流能力。

加分项

• 有自动驾驶、机器人、工业 AI 或矿山等非道路场景的数据与MLOps平台经验。

• 有 VLM / VLA 多模态数据、Demonstration Data、仿真数据或强化学习训练平台经验。

• 有大规模传感器数据、标注平台、数据质量或数据治理经验。

• 有 LLM / LLMOps、模型后训练或 AI 治理经验。

Posting Dates:

November 4, 2026 - November 19, 2026

Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply

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