- Company Name
- GSK
- Job Title
- Internship: GenAI/AI/ML Engineers & Data Scientists/Analysts (Master, PhD, Post-Doc), Belgium – 2025
- Job Description
-
**Job Title:** AI/ML GenAI Intern (Master’s/PhD/Post-Doc)
**Role Summary**
Develop and deploy machine learning, AI, and generative AI (GenAI) solutions to enhance vaccine research, manufacturing, and supply chain optimization. Collaborate on live projects across data science, AI engineering, and GenAI innovation.
**Expectations**
Enrolled in a Master’s, PhD, or Post-Doc program in Physics, Statistics, Engineering, Computer Science, or related fields. Minimum 4-month internship (3 months for exceptional candidates). Hybrid/full-remote availability; mandatory, curriculum-linked internship agreement required. Requires fluency in English and prior research/practical experience in AI, ML, or data science.
**Key Responsibilities**
- **Data Science:** Build predictive/interpretative models using ML/statistical tools; analyze structured/unstructured data for vaccine business insights.
- **AI/ML Engineering:** Develop autonomous AI systems, MLOps/DataOps pipelines, cloud/edge deployment, and scalable API/code solutions.
- **GenAI Engineering:** Design GenAI agents, RAG (Retrieval-Augmented Generation) systems, knowledge graphs; fine-tune LLMs and implement DevOps for cloud-based AI.
- Collaborate with science/business teams: Translate data into actionable insights; create user interfaces for model monitoring and business interaction.
**Required Skills**
- Advanced Python programming with GitHub portfolio (Python, PyTorch, AzureML, LangChain, FastAPI, etc.).
- Expertise in MLOps/MLops, data engineering tools (Azure, Git, Scikit-learn), and AI/ML frameworks.
- GenAI techniques: RAG, LLM fine-tuning, LangChain/Autogen agents, HuggingFace, Databricks.
- Problem-solving, agile project delivery, cross-functional communication, and adapting to dynamic research environments.
**Required Education & Certifications**
Active enrollment in a master’s, PhD, or post-doctoral program in quantitative or technical disciplines (Physics, Statistics, Computer Science, Mathematics). No certifications required.