Beijing, China
Open 5 months, first seen by us 157 days agoBuild and evaluate GenAI and AI use cases using LLMs and statistical machine learning
Lead rapid proof-of-concept AI builds, from scoping to demonstration
Hand successful prototypes to application teams for production
Build and maintain data pipelines for AI model training and deployment
Contribute to foundation infrastructure for future data and GenAI use cases
Design, develop and deploy, as well as evaluate Generative AI, AI and Data use case applications
Take full ownership of the PoC development lifecycle, from initial concept to demonstration.
Work with applications teams to transition successful PoCs into production-ready AI applications
build and maintain robust data pipelines to ingest, process, and transform large datasets from various sources
Contributing to the development and maintenance of foundation infrastructure to enable future data, AI & GenAI use cases.
Qualifikationen Qualification •Bachelor or Master’s in a quantitative degree (Computer Science, Engineering, Physics, Maths) or equivalent professional experience •6+ years experience in related technical field (software engineering, data engineering, data science) •Strong proficiency in software development principles, data structures, algorithms, and design patterns. •Strong Expertise in programming languages commonly used in AI/ML development (Python, Java, Scala, etc.) •Familiarity with LLM application stack (e.g. Langchain, Dify, 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 •Strong optimization modelling and statistical modelling experience and data aggregation skills, being an expert in analyzing large, complex, multi-dimensional data sets. •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.
Open 5 monthsWe first saw this posting 157 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 157
Up longer than most. Similar jobs usually come down between day 4 and day 77.
Well past Mercedes-Benz Group’s usual: its jobs come down by about day 28.
From 51 similar postings that came down, and 79 of Mercedes-Benz Group’s. Coming down is not always a hire.
17 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Qualifikationen Qualification •Bachelor or Master’s in a quantitative degree (Computer Science, Engineering, Physics, Maths) or equivalent professional experience •6+ years experience in related technical field (software engineering, data engineering, data science) •Strong proficiency in software development principles, data structures, algorithms, and design patterns. •Strong Expertise in programming languages commonly used in AI/ML development (Python, Java, Scala, etc.) •Familiarity with LLM application stack (e.g. Langchain, Dify, 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 •Strong optimization modelling and statistical modelling experience and data aggregation skills, being an expert in analyzing large, complex, multi-dimensional data sets. •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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New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
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.
•Lead Rapid Prototyping and PoC Delivery: Lead the 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.
•Responsible for contributing to and sharing best practice, know-how and participating in relevant technical discussion and governance forums in a subject matter expert capacity.
•Continuously research and evaluate new AI technologies and techniques to ensure Mercedes-Benz China remains at the forefront of AI innovation.
Job designation
•Design, develop and deploy, as well as evaluate Generative AI, AI and Data use case applications through application of LLMs (and other generative models), statistical machine learning techniques and data analytics.
•Lead the rapid development of Proof-of-Concept (PoC) AI applications to demonstrate value and feasibility:
- Take full ownership of the PoC development lifecycle, from initial concept to demonstration. This includes understanding the business problem, defining the scope of the PoC, and identifying key success metrics.
- Design and implement AI-powered prototypes quickly and efficiently, leveraging existing tools, frameworks, and cloud resources to accelerate development.
- Evaluate and select the most appropriate AI/ML algorithms, tools, and technologies for each PoC, considering factors such as performance, scalability, and cost.
- Train and evaluate AI/ML models using appropriate techniques, and iterate on model design to achieve desired performance.
- Work closely with business stakeholders, and other engineers to gather requirements and incorporate feedback into the PoC.
- Identify and mitigate potential risks associated with the PoC, such as data availability, model performance, and integration challenges.
- Work with applications teams to transition successful PoCs into production-ready AI applications, ensuring scalability, reliability, and maintainability.
•Identify and acquire relevant data sources for designed AI solutions and build and maintain robust data pipelines to ingest, process, and transform large datasets from various sources.
•Contributing to the development and maintenance of foundation infrastructure to enable future data, AI & GenAI use cases.
•Contributing to and sharing best practice, know-how and participating in relevant technical discussion and governance forums in a subject matter expert capacity. Stay up-to-date with the latest advancements in AI and related technologies.
Qualification
•Bachelor or Master’s in a quantitative degree (Computer Science, Engineering, Physics, Maths) or equivalent professional experience
•6+ years experience in related technical field (software engineering, data engineering, data science)
•Strong proficiency in software development principles, data structures, algorithms, and design patterns.
•Strong Expertise in programming languages commonly used in AI/ML development (Python, Java, Scala, etc.)
•Familiarity with LLM application stack (e.g. Langchain, Dify, 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
•Strong optimization modelling and statistical modelling experience and data aggregation skills, being an expert in analyzing large, complex, multi-dimensional data sets.
•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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Beijing, China
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