Research Scientist - #945586
kausable

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.
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.
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