The Opportunity QuoIntelligence turns millions of raw signals into finished Cyber Threat Intelligence (CTI) that security teams across Europe act on every day. The ML layer is what makes that possible: classification and enrichment today, AI-powered analysis through Agent Karla next. The ML team is small (2 people today), and the infrastructure is lean. You will own end-to-end production systems, from improving existing NLP pipelines, fine-tuning LLMs, building evaluation frameworks, and orchestrating AI agents in the cyber domain. What you ship, customers see. What You'll Do - Improve the production ML stack. The enrichment and classification pipelines work and serve real customers. They were built for speed, not longevity, so there's room to improve them. You'll ship at least one measurable improvement in your first 90 days. - Own model evaluation end-to-end. Quality metrics, ground truth labeling, offline/online evaluation: you'll design the framework the team uses to measure whether models are working in production. - Ship something the stack can't do today. The existing pipelines handle classification and enrichment. What comes next is open. You'll propose your first project in your first quarter, build it, and measure whether it works. - Expand agent capabilities. Help grow Agent Karla's intelligence by building new orchestration patterns and retrieval strategies using open-source frameworks like LangGraph. - Work directly with the IntelOps team. Your models serve the intelligence operations team; you'll validate performance against real-world threat scenarios, not benchmarks. AI-First in Engineering AI fluency is a company-wide standard at QI, not a department initiative. For engineering, three principles define the bar: - You build with AI-assisted tools daily (Cursor, Claude, whatever makes you faster). But you also know when AI-generated code introduces risk. You can evaluate whether an AI suggestion is reliable in a security-critical codebase, and you understand the difference between shipping fast and shipping recklessly. At a cybersecurity company, that judgment matters more than speed. - You evaluate new AI tools critically, adopt what works, and drop what doesn't. You have opinions on which tools are good and why, grounded in your own usage, not in what you read on LinkedIn. - Every model and pipeline has a clear definition of success before it ships. AI accelerates the iteration loop. Without clear success criteria, that speed is wasted. What You'll Bring Must-haves: - Production ML deployment. You've taken models from notebooks to production and maintained them over time, as part of systems that serve real users. - NLP and LLM grounding. Text classification, NER, summarization, embeddings, transformer-based models. You understand the fundamentals well enough to choose the right approach for a given problem, not just the newest one. - Comfort with messy data. Unstructured text with noisy, inconsistent signals. If your ML experience is limited to clean benchmark datasets, this role will frustrate you. - Python: It's the team's language. - Open-source mindset. You've worked with Hugging Face, spaCy, OpenNMT, or similar. If your entire career has been inside proprietary ecosystems with no exposure to open-source equivalents, that's a blocker. - AI fluency. Active daily use of AI-assisted development tools. You can show something you built or completed using AI, not just tell us you're interested. Nice-to-haves: - Experience with agent frameworks (LangGraph, LangChain, or similar) and orchestration patterns (ReAct, tool-calling, multi-agent systems) - Fine-tuning experience with open-source models (Qwen, LLaMA, Mistral) - Experience with inference servers and popular backends (e.g. NVIDIA Triton, vLLM, etc) - Familiarity with data orchestration tools (Kestra, Airflow, Prefect) - Cybersecurity or threat intelligence domain knowledge (genuinely not required; curious ML engineers ramp fast) What We Offer A small team where your work hits customers. No layers between your model and the intelligence product that clients rely on. Ownership, not just tickets. Your team lead defines priorities; you own how to solve them. You'll review the full service stack and model portfolio, then decide what to change and execute independently. Constraints that force creativity. We believe in using the simplest solution that gets the job done. We keep things lean and pick tools carefully. The interesting problems here come from making that work: squeezing more out of distilled models and designing pipelines smart enough to ship on the available hardware. Ethical red lines. QI holds the "Cybersecurity Made in Europe" label and serves as ENISA (the EU's cybersecurity agency) partner. We're upfront about what our AI can and can't do, and our compliance record backs it up. In a market full of AI hype, that credibility is a real advantage. Growth trajectory. Pre-Series A, revenue growing fast, Series A planning underway. You'd be shaping the ML direction for a company that still has ~40 people. The Process - Recruiter Screen - AI fluency screen - Take-home task: a real evaluation problem from the team's work. You can use AI tools, but you'll defend your reasoning and choices in the next round. - Hiring manager interview: walk through the task, then broader technical and behavioral assessment. A team member may join. - CEO/CTO Interview - Offer and Background Check We welcome applications regardless of gender, nationality, ethnic origin, religion, disability, age, or sexual identity. Diversity is key to producing high-quality intelligence.

Role Description Wir suchen einen Senior Shopware Entwickler mit Shopware 6 Erfahrung & AI Affinität, der transparente Kommunikation, sauberes Coding und qualitativ hochwertige Arbeit nicht nur als Floskel verwendet. - Konfiguration und Weiterentwicklung komplexer Shopware Projekte - Ein Mix aus Backend und Frontend – JavaScript (Vue.Js, React), PHP (Symfony), Git - Technische Verantwortung in Projekten und enge Zusammenarbeit mit Projektmanagern - Entwicklung von innovativen Ideen für den E-Commerce - Erkunden und Lernen von modernen und neuen Webtechnologien Qualifications - mind. 2-5 Jahre praktische Erfahrung im Full-Stack-Development - Mind. 1 Jahr Erfahrung in Shopware 6 - mind. Niveau B2 in der deutschen Sprache - Fundierte Kenntnisse in PHP (Symfony) - Erfahrung mit JavaScript-Frameworks wie Vue.js oder React - Routine im Umgang mit Git - AI-Affinität - auf dem neusten Stand mit AI Tools & Lust mehr dazuzulernen - Verantwortungs- und Qualitätsbewusstsein - Lösungsorientierte und selbstständige Arbeitsweise - Ausbildung zum Fachinformatiker/Anwendungsentwickler oder Bachelor Studium in Bereichen wie Mathematik & Computer Science Benefits - 100 % remote - Hands-on, strukturiert und lösungsorientiert – mit Fokus auf technischer Automatisierung und Effizienz - Kein Prozesschaos - Unsere Dokumentation und Abläufe sind digital und effizient - Individuelle Ziel- & Gehaltssysteme - Von BahnCard bis WalkingPad - Koro, Zalando, FC Moto, Wöhrl – 80–90 aktive Kunden, unter anderem aus Werbung auf ProSieben oder Höhle der Löwen - Du entscheidest - minimaler bis starker Kundenkontakt - Weiterbildungsmaßnahmen gehören für uns zum Alltag - Abwechslungsreiche Aufgaben und Projekte - Wir leben Feedback und fördern dies! - Teamspirit wird bei uns großgeschrieben – inklusive Nerfgun und lustige Memes Company Description Shopware Agentur 8mylez - Deine Experten aus Paderborn, Deutschland. Begleite uns auf dem Weg zur besten Shopware Agentur!

• Research, design, and develop innovative generative AI models and algorithms. • Implement and optimize deep learning architectures for generative tasks, focused on text generation. • Collaborate with cross-functional teams to define goals, requirements, and deliverables and implement the features. • Train and fine-tune models using large-scale datasets and advanced techniques. • Evaluate and assess model performance, making necessary adjustments to improve results. • Stay up-to-date with the latest advancements in generative AI trends and tools and contribute to the team's knowledge base. • Write clean, efficient, and maintainable code, following best practices and coding standards. • Document research findings, methodologies, and technical specifications. • Participate in code reviews and provide constructive feedback to peers. • Contribute to the development of tools and frameworks to facilitate generative AI research and development. • Interpret insights from our pre-sales, sales, customer success teams and clients to create AI-based features.

About Hach Hach is a world leader in the manufacture and distribution of analytical instruments, chemistry, software, and services for testing the quality of water, aqueous solutions, and air. Our products are designed for quality, accuracy, and simplicity. We are committed to providing reliable instrumentation, proven methods, and outstanding support. Working at Hach offers robust career development in a team-centric, growth-oriented environment. Hach Mission Ensure water quality for people around the world. Hach Vision We make water analysis better—faster, simpler, greener, and more informative—through unsurpassed customer partnerships, knowledgeable experts, and reliable, easy-to-use products. Job Title: AI Developer –Agents Location: Remote. GCRF Level: Contingent Employment Type: Contract Role Role Overview As an AI Developer, you will design, build, and optimize intelligent agents within the Microsoft Copilot ecosystem. You’ll collaborate with cross-functional teams to deliver scalable, reliable, and secure AI solutions that enhance productivity and decision-making across the organization. Responsibilities - Develop, test, and deploy Copilot based AI agents using Microsoft AI frameworks and APIs. - Collaborate with business stakeholders to implement requirements with agent capabilities. - Integrate Copilot agents with enterprise data sources and SaaS platforms. - Ensure agents comply with security, privacy, and ethical AI standards. - Monitor agent performance and implement continuous improvements. - Document agent architectures, workflows, and best practices. - Troubleshoot and resolve issues in production environments. - Stay current with advancements in AI, LLM, and Microsoft 365 technologies. Focus & Success Looks Like: - Ownership of agent development lifecycle and delivery of robust solutions. - Effective cross-functional collaboration with product, IT, and business teams. - Deployment of agents that drive measurable productivity or process improvements. - Proactive identification and resolution of technical challenges. - Clear documentation and knowledge sharing. Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. - 3+ years f experience in software development. - 1-3 years of experience in AI development, preferably with Microsoft technologies. - Proficiency in Python, Copilot SDKs , and experience with Azure AI, OpenAI, or other LLM frameworks. - Familiarity with enterprise data integration and API development. - Strong problem-solving and communication skills. - Ability to work independently and drive strategic initiatives. What We Offer - Ownership of high-impact AI projects. - A collaborative, innovation-driven culture. - Professional development and growth opportunities. - Competitive compensation and benefits. At Veralto, we value diversity and the existence of similarities and differences, both visible and not, found in our workforce, workplace and throughout the markets we serve. Our associates, customers and shareholders contribute unique and different perspectives as a result of these diverse attributes. Unsolicited Assistance We do not accept unsolicited assistance from any headhunters or recruitment firms for any of our job openings. All resumes or profiles submitted by search firms to any employee at any of the Veralto companies, in any form without a valid, signed search agreement in place for the specific position, approved by Talent Acquisition, will be deemed the sole property of Veralto and its companies. No fee will be paid in the event the candidate is hired by Veralto and its companies because of the unsolicited referral.