Intern_自动驾驶数据产线Agent开发实习生 ID21
招聘时间
即日起 至 2026-12-31
招聘单位
梅赛德斯-奔驰
所在地区
上海
工作地点
上海市/上海市/浦东新区
学历要求
硕士
实习时长
每周5天，每天6小时
职责描述
[6 months, 4-5 days/week]
Name of Project: AD Data Pipeline Agentic Systems Intern - 自动驾驶数据产线Agent开发实习生
Objectives:
Mercedes-Benz is developing scalable data pipelines to support autonomous driving. This project introduces LLM-based agents and intelligent automation across the data lifecycle, including data ingestion, processing, annotation, quality validation, and delivery. You will help design and implement agent workflows, internal tools, and system integrations to improve efficiency, reduce manual work, and enhance process reliability.
Main Tasks:
- Design and implement LLM-based agentic workflows for data ingestion, cleaning, annotation dispatching, quality assurance, and other repetitive data-pipeline tasks. Deliver working prototypes and reusable workflow components (30%)
- Build and maintain internal toolchains, CLI utilities, and automation services to improve developer&operator productivity (25%)
- Integrate agents with existing data platforms, labeling systems, CI/CD pipelines, and cloud services through well-defined tools and interfaces (20%)
- Implement robust orchestration logic, incl. error handling, retry mechanisms, human-in-the-loop escalation, logging, monitoring, and execution traceability (15%)
- Evaluate and benchmark agent performance, iterate on prompts and tool definitions, and document technical designs, evaluation results, and development best practices. (10%)
Qualification:
• Bachelor/Master student in Computer Science, Software Engineering, AI, or related field
• Good Python programming skills
• Experience with LLM APIs, prompt engineering, tool calling, and agent workflows
• Familiar with agent frameworks such as LangChain, LangGraph, CrewAI, or AutoGen
• Comfortable with Linux, Git, CLI tools, and modern software engineering practices
• Strong analytical thinking, problem-solving, and self-learning abilities
[Preferred]
• Familiar with TypeScript, Go, Rust, or other programming languages
• Experience building internal tools, automation workflows, or CI/CD integrations
• Knowledge of workflow orchestration tools (Airflow, Prefect, Temporal, Dagster)
• Basic understanding of Docker, Kubernetes, AWS, Azure, or GCP
[Bonus]
• Experience with autonomous driving data (camera, LiDAR, sensor fusion, map data)
• Experience building MCP servers, tool-use agents, or multi-agent systems
• Open-source contributions related to AI agents, developer tools, or data engineering
Language:
Chinese: Proficient
English: Conversational
Name of Project: AD Data Pipeline Agentic Systems Intern - 自动驾驶数据产线Agent开发实习生
Objectives:
Mercedes-Benz is developing scalable data pipelines to support autonomous driving. This project introduces LLM-based agents and intelligent automation across the data lifecycle, including data ingestion, processing, annotation, quality validation, and delivery. You will help design and implement agent workflows, internal tools, and system integrations to improve efficiency, reduce manual work, and enhance process reliability.
Main Tasks:
- Design and implement LLM-based agentic workflows for data ingestion, cleaning, annotation dispatching, quality assurance, and other repetitive data-pipeline tasks. Deliver working prototypes and reusable workflow components (30%)
- Build and maintain internal toolchains, CLI utilities, and automation services to improve developer&operator productivity (25%)
- Integrate agents with existing data platforms, labeling systems, CI/CD pipelines, and cloud services through well-defined tools and interfaces (20%)
- Implement robust orchestration logic, incl. error handling, retry mechanisms, human-in-the-loop escalation, logging, monitoring, and execution traceability (15%)
- Evaluate and benchmark agent performance, iterate on prompts and tool definitions, and document technical designs, evaluation results, and development best practices. (10%)
Qualification:
• Bachelor/Master student in Computer Science, Software Engineering, AI, or related field
• Good Python programming skills
• Experience with LLM APIs, prompt engineering, tool calling, and agent workflows
• Familiar with agent frameworks such as LangChain, LangGraph, CrewAI, or AutoGen
• Comfortable with Linux, Git, CLI tools, and modern software engineering practices
• Strong analytical thinking, problem-solving, and self-learning abilities
[Preferred]
• Familiar with TypeScript, Go, Rust, or other programming languages
• Experience building internal tools, automation workflows, or CI/CD integrations
• Knowledge of workflow orchestration tools (Airflow, Prefect, Temporal, Dagster)
• Basic understanding of Docker, Kubernetes, AWS, Azure, or GCP
[Bonus]
• Experience with autonomous driving data (camera, LiDAR, sensor fusion, map data)
• Experience building MCP servers, tool-use agents, or multi-agent systems
• Open-source contributions related to AI agents, developer tools, or data engineering
Language:
Chinese: Proficient
English: Conversational
