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!
---
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.
Tasks
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.
Requirements
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
Benefits
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.