Software Development

kausable GmbH

1-10

kausable HQ

More paid time off than the statutory minimum.

Additional vacation days

A laptop and the software you need, provided by the employer.

Company laptop

A share in the company's success through equity or stock options.

Company stock options

Adapt your start and end times around your life and workload.

Flexible working hours

Work from home for part of your working week.

Home Office

Work fully remotely, from home or anywhere agreed.

Remote work

 Travel costs for your commute or work trips are reimbursed.

Travel expenses compensation

Courage

Creativity

Curiosity

Empathy

Honesty

Impact

Innovation

Passion

Respect

🟧 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
<ul>
<li>learns in-context from just a few examples,</li>
<li>opens up whole new domains and skills without retraining,</li>
<li>generalizes across tasks and modalities.</li>
</ul>
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.
<h2>Tasks</h2>
🔬 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
<ul>
<li>design and scale deep neural networks pre-trained on synthetic data for active learning and dynamic task solving,</li>
<li>develop new model architectures and datasets for real-world reasoning,</li>
<li>extend synthetic-data pipelines and evaluate across tasks and modalities,</li>
<li>collaborate on open-source initiatives and contribute to research publications.</li>
</ul>
<h2>Requirements</h2>
👀 We're looking for research scientists with a strong background in one or more of these topics:
<ul>
<li>Active Learning</li>
<li>Meta-Learning</li>
<li>Causality</li>
<li>Modelling of complex and evolving systems</li>
<li>Reinforcement Learning</li>
<li>Bayesian Learning, Bayesian Optimization</li>
</ul>
Our recommended qualifications are:
<ul>
<li>A PhD in ML, Physics, or equivalent - or MSc with exceptional experience</li>
<li>A strong grasp of causality, meta-learning, PFNs, and active inference</li>
<li>The ability to work independently and think from first principles</li>
<li>Hands-on experience with modern ML tooling and research workflows</li>
<li>An outcome-oriented mindset</li>
</ul>
Additional nice-to-haves you might bring:
<ul>
<li>Publications in NeurIPS, ICML, ICLR, ECCV/ICCV, or similar</li>
<li>Experience with graph-based models or synthetic data generation</li>
<li>Open-source contributions</li>
</ul>
<h2>Benefits</h2>
🫂 Our Culture
We are “Putting Science at the Core of AI.” – with all its curiosity, daringness, and humanity. That means, we
<ul>
<li>are scientists at heart, with a builder’s mindset,</li>
<li>are open to challenge, grounded in curiosity and respect,</li>
<li>welcome diverse perspectives and value thoughtful as well as open debate,</li>
<li>focus on outcomes and real-world impact,</li>
<li>create and foster an environment of support, inspiration, and freedom for everyone to do their best work.</li>
</ul>
🏆 Perks &amp; Benefits
<ul>
<li>Competitive salary + equity</li>
<li>Social insurances (statutory health, pension, etc.)</li>
<li>Conference travel</li>
<li>Flexible working hours with work-from-home options</li>
<li>Pragmatic and supportive coworkers</li>
</ul>
⚒️ Tools and Infrastructure
<ul>
<li>Python, PyTorch, PyTorch Lightning</li>
<li>Weights and Biases</li>
<li>Docker</li>
<li>RunPod</li>
<li>AWS</li>
<li>A high-end laptop of your choice</li>
</ul>
🫶 Sounds like it's for you?
-&gt; ☕ 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.

Research Scientist

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Agentic-AI Harness Engineer

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