Machine Learning Engineer (Generative AI) (m/f/d)

Pabolo is an innovative startup revolutionizing the film industry through AI-powered movie creation tools. Our mission is to empower everyone to become a movie director. We are seeking a dynamic Machine Learning Engineer to bring our generative video and audio models to the next level.


Do you want to contribute to a growing, dedicated team to create an awesome product the world has never seen? Do you love movies? Come to us and revolutionize the way we make movies!

You will be part of our machine learning team that takes care of the data pipeline, model design, training and inference. We work at the pulse of time with the latest generative models for image, video and audio. We rely on the latest frameworks and tools. It is important to us that every developer has an overview of the entire user experience and can make as many decisions independently as possible.


  • Proven academic track record in generative AI model development
  • Strong knowledge of ML frameworks (PyTorch, Jax or Tensorflow)
  • Practical experience in distributed training, profiling and optimization of machine learning architectures
  • Familiarity with the latest research (Diffusion models, Transformers, VQ-GAN etc.)
  • Several years of experience in setting up large-scale experiments and productionizing ML models


At Pabolo, you will join an innovative and rapidly growing company where you have the opportunity to shape and influence processes. We offer a dynamic work environment with plenty of autonomy and responsibility across a wide range of subject areas. Our offices are located in Karlsruhe, Germany.

We are a rapidly growing, ambitious team and we are pleased that we have aroused your interest. The position is designed for joining us in our offices on-site in Karlsruhe, Germany. If you enjoy developing the film creation of the future with us - let us know! We are looking forward to meeting you!

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logo Paramax Machine Learning Engineer Full-time Onsite 📍 Karlsruhe, Germany Apply Now
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