Hybrid AI Engineer

at Synergeticon GmbH

• Job title: AI Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: No Education Requirement
• Tech skills: Docker, PyTorch
• Location requirements: Hybrid, Hamburg, Germany

About the role

• AI Engineer developing advanced AI and computer vision systems for industrial automation at Synergeticon. Leveraging cutting-edge research to create production-ready solutions.

Responsibilities

• You confidently operate at the intersection of research and engineering, train models independently, translate cutting-edge research into prototypes, and integrate them into production-ready systems.
• Prototypical implementation of state-of-the-art research approaches and transfer of research into production-ready solutions
• Apply and further develop classical and deep learning–based computer vision methods
• Independently implement, train, and debug models using PyTorch
• Optionally contribute NLP expertise in addition to computer vision (T-shaped profile preferred)
• Work with real industrial camera systems (e.g., Lucid or comparable), if applicable
• Use Docker for development and deployment workflows

Requirements

• 3+ years of relevant professional experience or equivalent project experience (e.g., Master’s thesis in a deep learning–focused environment)
• Strong background in classical and deep learning–based computer vision
• Excellent proficiency in PyTorch (independent implementation, training, and debugging of models)
• Proven ability to translate research into functional prototypes and production-ready solutions
• Experience working with real industrial camera systems (e.g., Lucid or comparable) is a plus
• Solid understanding of machine learning fundamentals and the ability to critically evaluate research papers
• Experience with NLP and Large Language Models (LLMs) is a plus (T-shaped profile preferred)
• Strong interest in research and motivation to stay up to date with state-of-the-art developments
• Responsible and transparent use of AI tools — leveraging them to accelerate implementation while maintaining ownership of system logic and architecture
• Proactive mindset, high quality standards, and strong communication skills for stakeholder collaboration

Benefits

• Work on cutting-edge AI systems for real-world industrial and robotic applications
• High level of ownership and responsibility in technically challenging projects
• Strong connection between research and real-world deployment
• Opportunity to work with state-of-the-art technologies in Computer Vision, LLMs, Graph Systems, and Agentic AI
• Flexible working hours and hybrid work options
• Modern hardware and high-performance computing infrastructure
• Flat hierarchies and fast decision-making processes
• Collaborative, innovation-driven team culture