Lead AI Engineer (Cloud & Machine Learning)

Lead AI Engineer (Cloud & Machine Learning)

Position Overview

A European-based industrial research laboratory, part of a global digital technology organization, is seeking a Lead AI Engineer to join its Data Analytics and Machine Learning team.

The team develops advanced machine learning models, AI technologies, tools, and cloud-based services that support multiple business domains within the digital media and entertainment ecosystem. This role is well suited for a highly skilled software engineer with strong hands-on experience in building production-grade AI systems and leading technical initiatives.

Key Responsibilities

• Lead the definition, design, and evolution of architectures that deliver AI, data analytics, and machine learning capabilities through scalable cloud-based AI services.

• Drive initiatives to improve the performance, scalability, and robustness of cloud AI systems, including data engineering pipelines and machine learning algorithms.

• Actively contribute to the software development of AI technologies and cloud services.

• Ensure that all deliverables meet the highest standards of quality, including functionality, performance, reliability, and security.

• Support and guide other team members, helping to improve overall team productivity and technical excellence.

Required Qualifications

• Master’s degree in computer science, engineering, mathematics, physics, or a closely related scientific discipline.

• Proven experience in bringing AI and data analytics solutions into operational business use.

• Strong background in machine learning, including representation learning and embedding techniques.

• Hands-on experience with modern machine learning frameworks such as PyTorch or TensorFlow.

• Experience developing and deploying cloud-based services, particularly on major cloud platforms.

• Excellent software engineering skills with strong proficiency in Python.

Preferred Qualifications

• Experience with graph-based learning methods and/or large language models (LLMs).

• Familiarity with graph learning libraries (e.g., geometric deep learning toolkits).

• Experience with interactive visualization or prototyping tools such as Streamlit, Gradio, or Dash.

• Strong documentation skills, including the ability to produce clear, high-quality technical reports.

• Experience with standard software development and maintenance tools (e.g., version control platforms).

Personal Attributes

• Ability to work effectively in a multidisciplinary, international team and to mentor or support colleagues when needed.

• Strong curiosity and interest in AI, security, and emerging technologies.