Senior ML Research Scientist

Senior ML Research Scientist

Berlin, Germany | Hybrid, 3 days per week onsite

An ambitious AI research organisation is developing safe-by-design, non-agentic AI focused on understanding and predicting the world rather than acting upon it. As a Senior ML Research Scientist, you’ll work with researchers, mathematicians and ML engineers on advanced deep learning, large-scale models, experimentation and evaluation. This is a hands-on research role where you’ll help develop novel ML approaches and shape the technical direction of a genuinely different AI programme.

Key Responsibilities

• Design and implement novel ML approaches for complex research problems.
• Develop and run large-scale experiments and evaluate model behaviour.
• Adapt and fine-tune advanced and foundation models.
• Build rigorous evaluation methodologies and benchmarks.
• Analyse results and identify new research directions.
• Work closely with researchers, mathematicians and ML engineers.

Required Experience & Skills

Essential

• PhD in Computer Science, ML, Mathematics, Statistics or related field.
• Publications at NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR or similar.
• 3-8 years' experience in ML/deep learning research or industry.
• Hands-on experience developing and training ML models.
• Experience with large-scale models, foundation models or LLMs.
• Strong Python and PyTorch, JAX or TensorFlow skills.
• Experience designing experiments and evaluating ML models.
• Experience with distributed or large-scale ML workloads.
• Strong understanding of modern deep learning methodologies.
• Desirable: open-source contributions; AI safety, alignment, interpretability, robustness or model evaluation experience; Foundation model or frontier AI research experience; Probabilistic modelling, Bayesian methods or statistical ML; NLP, scientific ML or advanced model adaptation experience; Experience with distributed training/inference infrastructure.

Why Apply?

• Work on a fundamentally different approach to advanced AI, centred on safe-by-design, non-agentic systems.
• Contribute directly to research direction rather than simply implementing an established roadmap.
• Collaborate with a highly technical team of researchers, mathematicians and ML engineers.
• Tackle challenging problems across deep learning, foundation models and AI safety.
• Make a meaningful contribution to the development of safer AI and scientific discovery.

Apply now or send a copy of your CV, referencing the title and location, and with a short introduction to [email protected].

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