In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable generative models. A diffusion model consists of two major components: the forward diffusion process, and the reverse sampling process. The goal of diffusion models is to learn a diffusion process for a given dataset, such that the process can generate new elements that are distributed similarly as the original dataset. A diffusion model models data as generated by a diffusion process, whereby a new datum performs a random walk with drift through the space of all possible data. A trained diffusion model can be sampled in many ways, with different efficiency and quality.

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3 jobs · 2 companies · last seen 2 April 2026

There are currently 3 open roles in Berlin that mention Diffusion Models, posted by 2 companies. It frequently pairs with LLM, Natural Language Processing, Machine Learning. Seen most in AI/ML (1% of their roles).

Frequently asked questions

How many Diffusion Models jobs are available in Berlin right now?

There are currently 3 open roles in Berlin that mention Diffusion Models, posted by 2 companies. The board is refreshed multiple times a day — more frequently during Berlin working hours — so new roles can appear throughout the day.

Which companies in Berlin are hiring for Diffusion Models?

Companies currently listing the most Diffusion Models roles include: Amazon / AWS, Google.

What skills pair well with Diffusion Models?

Employers who ask for Diffusion Models also frequently require: LLM (100%), Natural Language Processing (100%), Machine Learning (100%), Python (67%), pandas (67%).

In which Berlin job roles is Diffusion Models most in demand?

Based on current listings, Diffusion Models appears most in: AI/ML (1%) roles.