About this job

AI engineer needed to implement the FFplus funding project. Project start: September 1st.

Funding project in cooperation with the AI ​​Center RWTH Aachen.

• Conception, implementation and scientific validation of core AI innovations
• Development of novel generative image models and training pipelines for architecture-specific use cases.
• Research into controllable, region- and material-based generation methods is a unique selling point of the platform.
• Conducting systematic experiments, benchmarking, and qualitative and quantitative evaluations.
• Close collaboration with product and engineering teams to translate research results into production-ready AI systems.
• Responsibility for the scientific substance of the research projects
• Positioning as the scientific heart of AI research within the core team.
• Mission: Conception, implementation, and scientific validation of core AI innovations. You are the scientific heart of the research projects.
• Conception and further development of the AI ​​core architecture for generative image models with a focus on architecture-specific use cases.
• Development, training and optimization of generative deep learning models (especially diffusion models, UNet architectures, transformer-based approaches, latent diffusion).
• Implementation and evaluation of fine-tuning and adaptation methods such as LoRA, DreamBooth-like procedures and domain-specific transfer learning.
• Research on controllable generation mechanisms, e.g. region-based control, material- and texture-based conditioning, and structure- and context-aware image synthesis.
• Building and maintaining scalable training and experimentation pipelines (e.g., PyTorch, GPU clusters, automated experiments).
• Systematic scientific validation of the developed models through benchmarking, ablation studies, and qualitative and quantitative evaluation methods.
• Analysis, preparation and curation of training and evaluation datasets in an architectural context.
• Documentation of research results and methodological decisions to ensure reproducibility and knowledge transfer.
• Close collaboration with the product, frontend and backend teams to translate research findings into production-oriented AI systems.
• Technical support for the application and implementation of research and funding projects (e.g. IGP, KMU innovativ, EU programs).
• Observation and evaluation of current research developments in the field of generative AI and derivation of relevant innovation potentials.

What we offer:

• Initially 100% remote (occasional team meetings in Cologne)
• A long-term employment prospect secured through subsidies.
• Direct influence on a pioneering deep-tech research project.
• Equity acquisition: The allocation of company shares is negotiable and part of the compensation package.
• Chance of CTO role.
• Competitive remuneration (negotiable).

Provided in cooperation with the Federal Employment Agency.

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