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YEAP 研发管培 - AI与数据工程师（上海） at Aumovio

Shanghai, Shanghai, China -

Full Time

Start Date

Immediate

Expiry Date

29 Mar, 26

Salary

0.0

Posted On

29 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Linux, Docker, Microservices, gRPC, REST API, Automation Scripting, Python, Bash, Cloud Native Technologies, Machine Learning, PyTorch, TensorFlow, Model Optimization, Computer Vision, Natural Language Processing

Industry

Motor Vehicle Manufacturing

Description

Company Description Since its spin-off in September 2025 AUMOVIO continues the business of the former Continental group sector Automotive as an independent company. The technology and electronics company offers a wide-ranging portfolio that makes mobility safe, exciting, connected, and autonomous. This includes sensor solutions, displays, braking and comfort systems as well as comprehensive expertise in software, architecture platforms, and assistance systems for software-defined vehicles. In the fiscal year 2024 the business areas, which now belong to AUMOVIO, generated sales of 19.6 billion Euro. The company is headquartered in Frankfurt, Germany and has about 87.000 employees in more than 100 locations worldwide. Job Description 硬性要求: IT架构基础: 1- 熟悉Linux环境开发，掌握Docker基础部署 2- 了解微服务通信原理（gRPC/REST API设计） 3- 能编写自动化脚本（Python/Bash） 4- 了解云原生技术概念（容器化/服务网格/持续交付） AI技术认知: 1- 理解机器学习全流程（数据清洗→模型训练→部署监控） 2- 熟悉PyTorch/TensorFlow基础API，完成过CV/NLP课程项目 3- 知晓模型优化核心概念（量化/剪枝/知识蒸馏） Qualifications 对口专业: 计算机科学与技术，软件工程，人工智能，电子信息工程，自动化潜力特质: 1- 在GitHub部署过完整AI应用（如Flask+PyTorch服务化案例） 2- 能解读经典论文算法（如ResNet/Transformer）并复现核心模块 3- 对AI工程化痛点有思考（如曾尝试优化模型推理延迟） Additional Information Ready to take your career to the next level? The future of mobility isn’t just anyone’s job. Make it yours! Join AUMOVIO. Own What’s Next. Legal Entity: Continental Holding China Co., Ltd. (0674) Referral Bonus : No Job flexibility: Onsite Job Leadership level: Leading Self Working time: Full Time

Responsibilities

The role involves developing AI and data engineering solutions within the company. Candidates are expected to work on the full machine learning process from data cleaning to model deployment and monitoring.