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AI Engineer

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Onsite

AI Engineer

梅赛德斯-奔驰租赁有限公司

AI Engineer

Skills

Data AnalysisMachine LearningAIAWSAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Beijing, China

Work mode:

Onsite

Published on:

18 August 2026

What they need


该职位来源于猎聘 Objective of Job: Contribute to the future of Mercedes-Benz in China by leading the charge in AI innovation – build innovative solutions, drive rapid prototypes, and scale AI to new heights. As part of the AI&Data Value team, the position is responsible to deliver data-driven and AI-powered solutions that help our organization to achieve efficiencies and that excite our customers.

  • Responsible for developing and evaluating Generative AI, AI and Data use case applications through application of LLMs (and other generative models), statistical machine learning techniques and data analytics to address key business challenges within Mercedes-Benz China.
  • Deliver Rapid Prototypes and PoCs: rapid development of Proof-of-Concept (PoC) AI applications to demonstrate value and feasibility.
  • Develop and deploy AI solutions that are scalable, reliable, and maintainable in a production environment.
  • Responsible for contributing to the development and maintenance of foundation infrastructure to enable future data, AI & GenAI use cases.
  • Design and implement robust data pipelines and infrastructure to ensure high-quality data availability for AI model training and deployment.
  • Vibe code digital solutions for the challenges in our day-to-day business and drive the solutions towards Enterprise-readiness. Qualification Bachelor or Master’s in a quantitative degree (Computer Science, Engineering, Physics, Maths) or equivalent professional experience 3+ years experience in related technical field (software engineering, data engineering, data science) Proficiency in software development principles, data structures, algorithms, and design patterns. Expertise in programming languages commonly used in AI/ML development (Python, Java, Scala, etc.) Familiarity with LLM application stack (e.g. Langchain, Dify,n8n, Huggingface, Pytorch) and techniques (e.g. RAG, Embeddings, Fine-tuning etc..) Familiarity with machine learning packages (sklearn, xgboost etc…) Solid theoretical fundamentals for statistical methods, machine learning and generative models Clear AI-first mindset with vibe-coding proficiency, not only blindly trusting the AI output but with strong capability to assess and guardrail the results on code level.

Experience with cloud platforms (Azure, AWS and/or AliCloud) and deploying AI solutions in the cloud. Communication and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.

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