Senior Research Scientist – Sovereign AI Research

About the role

Dream is building sovereign AI systems for governments, enabling nations to protect and act on their most critical data. As a Senior Research Scientist you will lead cutting‑edge research that underpins AI models designed to operate under strict national security constraints.

Key responsibilities

• Design and develop novel AI model architectures that are modular, composable, and incorporate compute governance from the outset.
• Conduct open research across multiple domains such as computer vision, natural language processing, reinforcement learning, graph learning, optimization, representation learning, and neurosymbolic AI.
• Collaborate with interdisciplinary teams of AI researchers, cyber operators, and government experts to translate research into practical, deployable solutions.
• Publish findings, contribute to internal knowledge bases, and stay abreast of emerging techniques that can be applied to sovereign AI challenges.

Required profile

• PhD or equivalent experience in a relevant AI field with a strong publication record.
• Depth of expertise in at least one of the listed research areas and the ability to work across multiple domains.
• Experience solving real‑world problems under constraints such as security, privacy, and limited compute resources.
• Excellent analytical and problem‑solving abilities, with a collaborative mindset.

Required skills

• Computer Vision (object detection, segmentation, vision‑language models, self‑supervised learning)
• Natural Language Processing / Speech (large language models, information extraction, multilingual transfer)
• Reinforcement Learning (MDPs, model‑based and model‑free methods, sim‑to‑real transfer)
• Graph Learning (GNNs, graph clustering, knowledge‑graph embeddings)
• Optimization (convex/non‑convex, combinatorial, Bayesian optimization)
• Representation Learning (contrastive, self‑supervised, multimodal alignment, meta‑learning)
• Neurosymbolic AI (differentiable theorem proving, ILP, causal inference)