Research Scientist - #945586

At kausable, we're pioneering a reasoning-first approach to AI, developing a foundation that's fundamentally different from Large Language Models. While today's models rely heavily on pattern matching and massive pre-training, we're focussing on logical reasoning and adaptability.

We are creating agentic AI that

• learns in-context from just a few examples,


• opens up whole new domains and skills without retraining,


• generalizes across tasks and modalities.

If you're an experienced researcher, smart, creative, and inspiring – you'll fit right in!

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Our Company

We just raised a large funding round with investors from Black Forest Labs (a pioneer in visual generation), tech experts, and a strong network of advisors and supporters.

Our research and development currently revolves around generating synthetic world data, training and validating deep-learning models, creating and facilitating capable embedders for various domains and modalities. You'll have the opportunity to

• design and scale deep neural networks pre-trained on synthetic data for active learning and dynamic task solving,


• develop new model architectures and datasets for real-world reasoning,


• extend synthetic-data pipelines and evaluate across tasks and modalities,


• collaborate on open-source initiatives and contribute to research publications.

We're looking for research scientists with a strong background in one or more of these topics:

• Active Learning


• Meta-Learning


• Causality


• Modelling of complex and evolving systems


• Reinforcement Learning


• Bayesian Learning, Bayesian Optimization

Our recommended qualifications are:

• A PhD in ML, Physics, or equivalent - or MSc with exceptional experience


• A strong grasp of causality, meta-learning, PFNs, and active inference


• The ability to work independently and think from first principles


• Hands-on experience with modern ML tooling and research workflows


• An outcome-oriented mindset

Additional nice-to-haves you might bring:

• Publications in NeurIPS, ICML, ICLR, ECCV/ICCV, or similar


• Experience with graph-based models or synthetic data generation


• Open-source contributions

Our Culture

We are “Putting Science at the Core of AI.” – with all its curiosity, daringness, and humanity. That means, we

• are scientists at heart, with a builder’s mindset,


• are open to challenge, grounded in curiosity and respect,


• welcome diverse perspectives and value thoughtful as well as open debate,


• focus on outcomes and real-world impact,


• create and foster an environment of support, inspiration, and freedom for everyone to do their best work.

Perks & Benefits

• Competitive salary + equity


• Social insurances (statutory health, pension, etc.)


• Conference travel


• Flexible working hours with work-from-home options


• Pragmatic and supportive coworkers

Tools and Infrastructure

• Python, PyTorch, PyTorch Lightning


• Weights and Biases


• Docker


• RunPod


• AWS


• A high-end laptop of your choice

Sounds like it's for you?

-> Send us your favorite way to drink coffee along with your CV or LinkedIn! We'll get back to you soon.

If it's a match, we'll get to know each other in one to three casual interviews.