About the job
Join Our Team as a Senior Machine Learning Engineer
Full-time | Munich | Seed Stage | Equity + Salary
At Knowlix, our mission is to revolutionize small business productivity by harnessing the power of AI. We aim to establish ourselves as the leading platform for human-AI and AI-to-AI collaboration.
As a member of our early-stage team, you will have the unique opportunity to influence our product development and help shape a platform that could serve millions.
We prioritize speed and quality, embracing a culture of rapid iteration and continuous improvement. If you are passionate about leveraging AI to innovate and scale solutions, we want you on our team.
Why Choose Knowlix?
Backed by prominent investors, we are a well-funded startup with ambitious goals.
Our technology is already making waves with early adopters experiencing its benefits.
We are tackling a vast market with a product designed to redefine workplace collaboration.
As one of the first hires, your contributions will have a significant impact on our success.
We believe that focused iteration is key to rapid development.
This is not just a job; it's your chance to help create a lasting legacy.
Your Role
You will be responsible for designing and deploying cutting-edge machine learning systems, specifically focusing on LLM-driven agents and self-optimizing workflows. This hands-on position will require you to develop robust data pipelines, foster rapid experimentation, and ensure continuous model enhancement in a dynamic startup environment.
Your Responsibilities
Create LLM-based agents, implement tool-using workflows, and design autonomous self-improvement systems.
Design, train, and assess machine learning models in the areas of NLP/LLM, computer vision, and data retrieval.
Build data pipelines, develop training code, and create tools for experimentation and automated deployment.
Utilize PyTorch for model development and tools like Weights & Biases for experiment tracking.
Implement performance monitoring, including oversight for drift and safety measures.

