Senior ML Research Scientist
We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda.
We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda.
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Wir schreiben dir, sobald eine neue geprüfte Stelle in Berlin dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
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Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
and qualifications - Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but not required if the candidate demonstrates exceptional abilities. - 5+ years of experience in deep learning research projects, in particular with frontier models. - Proven experience in the training, adaptation, and/or fine-tuning of frontier models across a variety of complex scenarios that involve, for example, transfer learning, domain adaptation, or meta learning. - Expertise in the integration and use of ML libraries such as PyTorch, TensorFlow, or JAX for the development, training, and evaluation of ML models, ideally in distributed computing environments. - Strong experience in Python software development, in the use of version control, collaboration tools, and experiment management and tracking tools. - Strong communication skills, both written and verbal, with the ability to exchange ideas with researchers across different disciplines. - Ability to work collaboratively in a team environment while also being self-motivated and independent. Preferred skills and qualifications - Experience analyzing the behavior of frontier models in safety-critical contexts. - Experience in the design and development of model alignment strategies or benchmarks. - Experience with natural language processing or probabilistic graphical models. - A track record of contributing to high-quality research projects in deep learning.
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.
We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda. In this role, you will design and implement innovative ML models aimed at solving advanced AI safety problems. Key responsibilities - Propose, design, and implement novel ML models tailored to solve complex AI safety problems. - Collaborate with mathematicians and other specialized research scientists to integrate theoretical advancements into practical ML algorithms and models. - Adapt and fine-tune existing frontier models to enhance their applicability to specific settings. - Design and implement experimental protocols and evaluation frameworks to validate hypotheses and ensure robust and reproducible results, including at the scale and complexity of frontier models. - Analyze and interpret experimental data in order to steer future research questions and objectives. - Benchmark and optimize model performance and efficiency along with ML engineers to ensure the optimal usage of computing resources over the course of long experiments. - Communicate findings and synchronize work with other researchers and engineers.
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Zur Originalanzeige222 geprüfte Stellen bei 138 Arbeitgebern, 29 davon ortsunabhängig. 91 in der KI-Entwicklung, 70 in Integration & Automatisierung.