Mathematical Scientist for AI Safety Research
Entwickelt theoretische Rahmenwerke und Architekturen für sichere KI-Systeme und beweist probabilistische Sicherheitsgarantien unter Daten- und Rechenbeschränkungen.
Entwickelt theoretische Rahmenwerke und Architekturen für sichere KI-Systeme und beweist probabilistische Sicherheitsgarantien unter Daten- und Rechenbeschränkungen.
Entwirft und betreibt GPU-Cluster und Deployment-Pipelines, bringt KI-Modelle in Produktion und überwacht Modell- sowie Infrastrukturleistung.
Own and Evolve Our Infrastructure – You take ownership of our AWS and Hetzner environments and evolve them further – everything as Infrastru
Data Scientist DEPT®/AI has a single mission: to make the best work in the industry using AI to enhance everything we do.
sensmore is a Berlin/Potsdam-based robotics startup delivering production-proven automation for industries where the world’s raw materials a
Wir schreiben dir, sobald eine neue geprüfte Stelle in Berlin dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
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Betreibt und skaliert GPU-Cluster für das Training tabellarischer Foundation Models, inklusive Scheduling, Kostenoptimierung und CI/CD-Pipelines.
work as part of our Outbound Data Science team to further optimize our innovative product based on machine learning and artificial intellige
Build and Ship AI Agents - Design and build agents that automate complex finance workflows.
Bringt jedes TabPFN-Modell-Release über SAP, Cloud-Marketplaces und Kundenumgebungen live und koordiniert dafür Engineering und Partnerteams.
We re a Data Team that operates like a scaleup within an established company: real ownership, short decision paths, and room to shape things.
& THE TEAM Join our dynamic Logistics Network Planning team, where you’ll be at the forefront of shaping the future of Zalando’s logistics operations.
Make an Impact by: - Delivering AI and ML solutions that solve real business problems and create measurable value for teams across DCS - Own
Build and ship models that predict user value, engagement, and reward behaviour.
Die KfW nutzt Cloud-Technologien, um Anwendungen mit Künstlicher Intelligenz umzusetzen.
German (C1+) and English required You make sure 10+ software companies get real value out of AI.
Job Title: System Integrator / Software Engineer – Robotic Hand (m/f/d) Location: Berlin, Germany Why this role matters Having secured disru
Baut Signierung, Provenienz und Delta-Updates für KI-Modelle als versionierte Pakete und testet sie auf echter Robotik-Hardware.
Analyse und Identifikation von AI-Use-Cases in Kundenumgebungen Bewertung aktueller AI-Technologien und -Plattformen, prüfen von Lösungskonz
Airteam is a Berlin-based SaaS startup with an AI-powered cloud platform for roofers and solar planners.
Entwirft und betreibt On-Prem- und Hybridplattformen für AI/ML-Workloads auf Kubernetes/OpenShift und verantwortet deren Sicherheit und Compliance.
Multi-Agent-Architektur & Orchestrierung Konzeption und Umsetzung produktionsreifer Multi Agent Systeme mit klar definierten Strategien für
Du treibst Projekte unermüdlich von der Idee bis zur Umsetzung, um den Vertrieb in der Sparkassen Finanzgruppe zu unterstützen Du setzt KI-T
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Warum dieser Job gelistet ist
Kernaufgabe ist die Forschung an KI-Architekturen und Sicherheitsmechanismen für Modelle; ohne KI fehlt der Kern der Stelle.. Prüfverfahren ansehen
The ability to regularly travel alongside Yoshua and team members to conferences is a big plus, as it will significantly accelerate the work! About LawZero LawZero is a non-profit organization committed to advancing research and creating technical solutions that enable safe-by-design AI systems. Its scientific direction is based on new research and methods proposed by Professor Yoshua Bengio, the most cited AI researcher in the world.
Based in Montreal, LawZero’s research aims to build non-agentic AI that learns primarily to understand the world rather than to act in it, giving truthful answers to questions based on transparent and externalized probabilistic reasoning. Such AI systems could be used to accelerate scientific discovery, to provide oversight for agentic AI systems, and to advance the understanding of AI risks and how to avoid them. LawZero believes that AI should be cultivated as a global public good—developed and used safely towards human flourishing.
For more information, visit You belong here At LawZero, diversity is important to us. We value a work environment that is fair, open and respectful of differences. We welcome applications from highly qualified individuals interested in working towards our mission in a respectful, inclusive and collaborative setting.
Your personal information will be collected and processed by LawZero to evaluate your application for employment in compliance with our Privacy Policy. Under privacy laws in force in your country of residence, you may have several privacy rights, such as to request access to your personal information or to request that your personal information be rectified or erased. Details on how you can exercise your rights can be found in our Privacy Policy.
Frontier AI companies are throwing billions of dollars into scaling existing architectures and methods such as next-token-prediction, direct preference optimization (DPO), reinforcement learning with human feedback (RLHF), and reinforcement learning with verified rewards (RLVR). These methods are very powerful, yet fundamentally flawed, resulting in misalignment, sycophancy, systematic biases, and other forms of harmful behavior that are already having severely negative consequences in our society. LawZero is a non-profit founded by Yoshua Bengio developing a fundamentally new approach, the Scientist AI.
We are inspired by the fact that scientific theories are both generally useful and, unlike an untrusted agent, equivariant to the consequences of their use (for a broad overview, see our blogpost). We aim not only to build a novel, safe-by-design system, but to construct a theoretical blueprint for safe AI systems, which are at once capable and come with probabilistic safety guarantees, under finite data and compute constraints. We are seeking an outstanding theoretical researcher to contribute to the foundational and theoretical efforts here working with Yoshua Bengio and our world-class team of researchers and engineers.
Key responsibilities - Boldly go where no one has gone before in exploring new AI system architectures, theoretical frameworks, and new safety mechanisms in search of a blueprint for safe AGI and corresponding safety guarantees. - Work closely with Yoshua Bengio and other leading researchers to analyze and refine the formal requirements needed to safely build and deploy the Scientist AI, including proving probabilistic safety guarantees under finite data and compute constraints; and, as the system matures, helping our research teams with empirical validation. - Analyze, evaluate and contribute to the existing theoretical work already undertaken at LawZero by Yoshua Bengio and leading researchers, including the writing and dissemination of scientific papers. - Read vigorously to stay up-to-date with relevant AI safety and machine learning research and deeply understand the risks posed by frontier models, including misalignment, reward hacking, instrumental goals, etc. - Scrutinize and contribute to LawZero’s broader research agenda in order to guide and prioritize experiments to answer critical safety questions efficiently, in a way that does not prevent the highest level of capability. - Share your knowledge about AI Safety and help researchers and engineers at LawZero better design and implement new ML algorithms and experiments. Skills and qualifications - A PhD in machine learning, computer science, mathematics, statistics, or an adjacent area relevant to the Scientist AI research program. - A track record of research, especially in the formalization and fruitful technical analysis of subtle natural-language intuition. - Strong interest and ideally experience with technical AI safety, including an exceptional ability for abstract systems thinking. - A deep understanding of the mathematical underpinnings commonly used in the design and analysis of probabilistic machine learning, especially for neural networks and language models. - The perseverance to work through hard and ill-defined problems, and to use confusion and dead-ends as challenges to dig deeper and further understanding. - Clear communications: the ability to articulate complex ideas verbally and in writing to both technical and non-technical audiences. - The ability to work in a collaborative environment and contribute to collective research goals.
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Zur Originalanzeige204 geprüfte Stellen bei 134 Arbeitgebern, 24 davon ortsunabhängig. 82 in der KI-Entwicklung, 62 in Integration & Automatisierung.