Applied AI Engineer - China Campus Recruitment 2027

As an Applied AI Engineer, your role will encompass:

- Conducting ambitious projects in the transformation of clients through data & AI.

- Collaborating with the other Divisions (Activation, Creativity, and Strategy) to provide comprehensive

services to your clients.

- Developing privileged relationships with our clients, using your technical abilities to assist in the

transformation of their organisation.

Among your responsibilities as an Applied AI Engineer, you will be responsible for:

Delivering data & AI projects

• →Securing delivery on your projects.
• →Communicating your work and achievements among the team.
• →Working closely with your Consulting counterpart to build and maintain strong relationships with your clients and best understand their needs.
• →Ensuring that your solutions bring value to the client’s business problem.
• →Applying statistics, machine learning and agentic solutions where they are the right answer to the client’s question, from framing the problem to validating the result.
• →Being a good team player, knowing your role and responsibility in the global ambition.

Building AI / agentic solutions for clients

• →Designing and building AI solutions — machine learning models, large language model agents, retrieval, tool calling, orchestration and workflow automation — that solve concrete business problems.
• →Taking these solutions into production inside the client’s environment: their data platforms, their infrastructure, their security and compliance constraints.
• →Designing, building, testing, deploying and evaluating these systems, and continuously improving them after go-live.
• →Working on site with client teams, business and technical, to turn requirements into technical designs, prototypes and shipped systems.
• →Documenting and handing over what you build, so the client’s teams can run and extend it.
• →Holding the engineering standard: version control, code review, testing and reproducibility.

Being a great tech person

• →Demonstrating the skill and credibility required to ensure the success of our clients’ initiatives.
• →Researching and developing new technical approaches to address problems efficiently.
• →Sharing best practices and contributing to Artefact’s institutional knowledge.
• →Turning field experience into reusable assets — accelerators, templates and evaluation libraries — that other teams can pick up.
• →Embodying Artefact’s values and inspiring others to do the same.

• A Master’s degree in machine learning, mathematics, computer science, or related fields.
• At least 1 year of hands-on experience developing and applying data-driven solutions in a corporate or consulting setting, preferably in a consumer marketing context (experience in the AI industry is a plus).
• Strong knowledge of data processing, data modeling, algorithms, and data architecture.
• Strong grounding in statistics and machine learning: statistical analysis and inference, experiment design and measurement, model training, evaluation and interpretation.
• Hands-on experience building solutions on top of large language models: prompt and context design, retrieval-augmented generation, tool calling, agentic workflows and orchestration.
• Solid software engineering practice: version control, code review, testing and documentation.
• Ability to explain technical trade-offs to both business and technical stakeholders.
• Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritise, with an approach for maximum impact.

We believe data & AI is changing the world, and it’s just the beginning. We want this to be done in the right way, with transparency and ethics. This is the only way to create sustainable impact for business and society.

We are on a mission to build the next generation of data leaders who: 

• Fully capture the power of data & digital to deliver business value;
• Bring understanding, trust & transparency of data and AI into our society.

• Collaboration: People of different background and expertise working closely together;
• Trust & Transparency: Dealing with data topics with integrity and ethics; Realistic and honest with our capabilities and limitations;
• Innovation: Always working on the most trendy and new topics on data and digital; Always on top of the new ways of using data;
• Action: We would rather do than to tell what to do; Has a “building the plane while flying” agile mentality.

• We bring great value to business and create a better society with the understanding, transparency and ethical use of data and AI;
• We build the next generation of data leaders;
• We disrupt the market:
  • AI Native - A culture that encourages daily AI tool usage, experimentation, and continuous skill updates
  • ART + SCIENCE - Mixture of talents in ART (Creative, Planning, Media, Consumer Engagement) and SCIENCE (AI Strategy, AI Engineer, Data Engineer) ;
  • End to End - Capabilities from Strategize to Build to Run.