Software Engineer (Data & AI)

Objective of job

Contribute to the future of Mercedes-Benz in China by leading AI innovation, building innovative solutions, developing rapid prototypes, and scaling AI applications. As part of the AI & Data Value team, this role delivers data-driven and AI-powered solutions that improve organizational efficiency and customer experiences.

Responsibilities

• Develop and evaluate Generative AI, AI, and Data use-case applications using LLMs, generative models, statistical machine learning, and data analytics.
• Lead rapid development and delivery of AI proof-of-concept applications, from defining the business problem and success metrics through demonstration and production transition.
• Design, develop, deploy, and evaluate scalable, reliable, and maintainable AI solutions.
• Design and implement robust data pipelines and infrastructure for ingesting, processing, transforming, and supplying large datasets for AI model training and deployment.
• Contribute to the development and maintenance of foundation infrastructure for future data, AI, and GenAI use cases.
• Evaluate and select appropriate AI/ML algorithms, tools, technologies, and cloud resources based on performance, scalability, and cost.
• Train and evaluate models, iterate on model design, gather stakeholder feedback, and identify and mitigate proof-of-concept risks.
• Research emerging AI technologies, share best practices, and participate in technical discussions and governance forums as a subject matter expert.

Qualifications

• Bachelor’s or Master’s degree in a quantitative discipline such as Computer Science, Engineering, Physics, or Mathematics, or equivalent professional experience.
• At least 6 years of experience in software engineering, data engineering, data science, or a related technical field.
• Strong knowledge of software development principles, data structures, algorithms, and design patterns.
• Strong proficiency in programming languages used in AI/ML development, including Python, Java, or Scala.
• Familiarity with LLM application technologies such as LangChain, Dify, Hugging Face, and PyTorch, and techniques including RAG, embeddings, and fine-tuning.
• Familiarity with machine learning packages such as scikit-learn and XGBoost.
• Strong theoretical foundations in statistical methods, machine learning, and generative models.
• Experience with optimization and statistical modelling, data aggregation, and analysis of large, complex, multidimensional datasets.
• Experience with Azure, AWS, and/or AliCloud and deploying AI solutions in the cloud.
• Strong communication and interpersonal skills, including the ability to explain technical concepts to technical and non-technical audiences.

Benefits

• Flextime
• Possible hybrid work
• Health benefits
• Mobility offers
• Employee discounts
• Good public transport
• Barrier-free workplace
• Parking
• In-house doctor
• Canteen and café