Generative AI & ML Expert

We are looking for IT colleagues who are passionate about generative AI and machine learning, while maintaining a practical perspective on its application. You understand both the technological possibilities and limitations, and can distinguish hype from value.

As an AI Engineer, you listen to users, build intelligent solutions, and clearly explain what AI can achieve. You quickly see how LLMs and machine learning can make a difference — from document processing and content generation to systems that support customers.

Building a safe and usable AI application is not trivial.

Key Responsibilities:

• Working with advanced technologies: Python, PyTorch, TensorFlow, Transformers (GPT), MS Copilot, High Performance Computing, Claude, Gemini, LLaMA, and more.

• Researching how AI can be applied in a desirable, feasible, and safe manner within business processes, maintaining active and transparent dialogue with all stakeholders.

• Collaborating with IT teams and other stakeholders to identify and implement LLM-driven solutions for business processes (e.g., intelligent chatbots, summarizing specialized documents, automated reporting).

• Developing, training, optimizing, and managing neural networks and other machine learning models, both in the cloud and on on-premise HPC infrastructure.

• Ensuring compliance with data protection and privacy regulations (e.g., GDPR) and ethical AI principles (EU AI Act).

• Staying up to date with the latest developments in LLMs, Generative AI, and MLOps practices to guide infrastructure and service development

Requirements:

• Master’s degree in Artificial Intelligence, Data Science, Computer Science, or a related field, or equivalent experience.

• Preferably 5 years of professional ICT experience with broad and deep knowledge of AI technologies, machine learning, and data analysis.

• Practical experience implementing and managing LLMs (e.g., BERT, GPT, LLaMA) in production environments.

• Skilled in MLOps tools (e.g., Kafka, MLflow, Kubeflow, Airflow) or willing to learn them.

• Experience with on-premise infrastructure, including containerization (e.g., Docker, Kubernetes) and hardware optimization (e.g., GPU clusters).

• Knowledge of CI/CD pipelines and version control systems (e.g., Jenkins, Git).

• Strong understanding of data protection, privacy, and ethical AI considerations

Job Type: Full-time

Application Question(s):

• Current Salary?
• Expected Salary?
• When can you join?
• Portfolio Links

Work Location: In person