Neuro-Symbolic AI Research Scientist — Paris Frontier

Rippletide; Paris; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Relocation support

Healthcare

Generous paid leave

Office in central Paris

Job summary

Rippletide in Paris is seeking a Research Scientist specializing in Neuro-Symbolic AI to advance the theoretical and algorithmic foundations powering our hypergraph decision database. You will push the boundaries of neural learning fused with structured symbolic reasoning to enable robust enterprise AI agents.

You will publish in top venues and work closely with engineering to deploy research prototypes into production components, shaping world-model agents that reason under uncertainty.

Qualifications

• PhD in Computer Science, Machine Learning, or a closely related field with a focus in neuro-symbolic AI, knowledge representation, or automated reasoning.
• A strong publication record at top-tier ML/AI conferences demonstrating originality and rigor.
• Proficiency in Python and modern DL frameworks (PyTorch or JAX), plus experience implementing symbolic solvers or logic-based systems.

Responsibilities

• Conduct original research in neuro-symbolic AI, integrating neural networks with symbolic reasoning over hypergraphs.
• Develop novel algorithms for multi-hop inference, causal reasoning, and planning on large-scale knowledge representations.
• Design world-model agent architectures using hypergraph reasoning to manage beliefs, predict outcomes, and act under uncertainty.
• Publish findings in top venues (NeurIPS, ICML, ICLR, AAAI, KR) and contribute to the community via open-source work.
• Collaborate with Engineering to transition research prototypes into production-grade components.

Skills

Neuro-symbolic AI

Graph-based reasoning

Interdisciplinary collaboration

Education

PhD in Computer Science / ML or related

Tools

Python

PyTorch

JAX

Symbolic solvers

Job description

Rippletide in Paris is seeking a Research Scientist specializing in Neuro-Symbolic AI to advance the theoretical and algorithmic foundations powering our hypergraph decision database. You will push the boundaries of neural learning fused with structured symbolic reasoning to enable robust enterprise AI agents.

You will publish in top venues and work closely with engineering to deploy research prototypes into production components, shaping world-model agents that reason under uncertainty.