Machine Learning Platform Engineer – No-Code ML (m/f/d) in Stuttgart

RockQ Technologies is opening a new role focused on making machine learning accessible to everyone. You will design and build a framework that lets non-technical users create, train and deploy Machine Learning models inside our no-code platform, built for production environments.

RockQ Technologies (formerly NC-Vision) is a Stuttgart-based software pioneer specializing in the digital transformation of the manufacturing industry. We provide a state-of-the‑art, AI-powered no-code platform that bridges the gap between operational reality and digital innovation.By enabling domain experts to build complex enterprise applications through visual modeling — without traditional programming or specialized IT expertise — we help companies modernize legacy systems, integrate artificial intelligence and scale intelligent solutions worldwide.This is a rare opportunity to shape how an entire class of users — product managers, analysts, domain experts — interacts with ML for the first time, without ever writing a line of code.

Your Responsibilities

• Break down the key ingredients and moving parts of machine learning into clear, modular concepts that can be represented visually and manipulated by non-experts.
• Find simplifications in ML workflows and terminology without compromising the functionality, flexibility or correctness of the resulting models.
• Implement the basic building blocks (nodes, components, templates) needed to visually model machine learning networks and pipelines.
• Discover and design UI guidance, interaction patterns and visualizations that help non-technical users understand, configure and create machine learning models with confidence.
• Integrate the resulting solution into RockQ's broader no-code development platform, ensuring it works reliably in production environments alongside other platform features.
• Collaborate closely with product, design and engineering teams to iterate on the framework based on user feedback and real-world use cases.

Your Profile

• 5+ years of experience in software development, including designing and owning a system, framework or platform component end-to-end rather than working within one already defined by others.
• 3+ years of experience in Machine Learning, with strong knowledge of the techniques used to create and use machine learning models and how to train them.
• Demonstrated experience with software or framework architecture — designing abstractions, APIs or modular building blocks that others (here, non-technical users) will build on top of.
• Experience collaborating on, or directly designing, UX/UI for complex technical tools: you know how to turn expert workflows into interfaces a novice can use confidently.
• Familiarity with production ML systems (deployment, serving, monitoring): you understand what 'production-ready' means beyond a notebook or prototype.
• A high degree of independence in decision-making: comfortable defining ambiguous problems, weighing trade-offs between simplicity and flexibility, and making architectural and product calls with minimal precedent or oversight.
• Spoken and written proficiency in English.

What We Offer

• High business impact: your decisions will directly contribute to increasing production efficiency, driving digital transformation and creating measurable value for our customers.
• Exposure to industrial innovation: you will work with modern manufacturing technologies, including Industry 4.0, smart factory solutions and complex system integrations.
• A dynamic and innovative working environment with plenty of opportunities for personal growth, autonomy and direct impact on the further development of our products.
• A company culture built on respect, open feedback and sustainable ways of working, combined with attractive working conditions and a long-term perspective.
• A hybrid working model that combines collaboration in the office with the flexibility of remote work.
• A healthy work-life balance: at least 30 days of paid vacation per year, above the average offered by many employers and beyond the statutory minimum.

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