Research Scientist

🟧 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.