- Location
- Germany
- Workplace
- Hybrid
- Department
- IT
- Source
- JOIN
Description
At Synergeticon, we are shaping the future of industrial automation. We combine intelligent **computer vision, AI, and robotics solutions** with cutting-edge **data analytics and automation technology** to make production and logistics processes more efficient. Our goal is to develop **resilient, flexible, and seamlessly integrated automation systems** that intelligently reduce complexity.
For the past nine years, we have been working with **leading companies in the aviation, automotive, and logistics industries**. Our software solutions are based on **computer vision, AI, 3D reconstruction, LLM technologies, and automation systems**, which we directly integrate into industrial processes.
A key aspect of our projects is **3D reconstruction**, where we utilize camera streams to create **digital 3D models** and combine them with additional sensor data. This technology enables us to capture, analyze, and optimize **production environments and processes in detail**. Our solutions are applied in **manufacturing control, quality inspection, robotics, and digital production workflows**.
As a **Machine Learning Engineer**, you work on the development of robust perception and AI systems for industrial and robotic applications. 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.
## Aufgaben
We are looking for a broadly skilled profile across multiple AI disciplines, with deep expertise in at least one core area (e.g., Computer Vision, Deep Learning, or NLP).
Prototypical implementation of state-of-the-art research approaches and transfer of research into production-ready solution
- 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
## Qualifikation
- 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
- Experience in applied research or high-innovation industrial projects
- 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
