Research Scientist

 

kausable GmbH is 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, they are focusing on logical reasoning and adaptability.

 

They 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!

 

The Company

kausable 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.

 

Tasks

kausable's 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

 

Requirements

The start-up is 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

 

Recommended qualifications:

• 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

 

Benefits

kausable are 'putting science at the core of AI' – with all its curiosity, daringness, and humanity. That means, they:

• 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 and 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 kausable your favorite way to drink coffee along with your CV or LinkedIn profile! They will get back to you soon.

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