AI Research Scientist

Skyfall is building the first enterprise-scale World Model
.

Large language models have demonstrated impressive capabilities, but they remain fundamentally limited in reasoning about complex, dynamic systems over long horizons. Our mission is to overcome these limitations by developing counterfactual world models for planning: models that deeply understand the interplay and causal relationships between data, people, and processes inside organizations.

Skyfall was founded by the original Maluuba team — pioneers of the deep learning revolution — who worked closely with leaders such as Yoshua Bengio and Richard Sutton before Maluuba’s $160M acquisition by Microsoft, where it became Microsoft’s AI research center in Canada.

We are building the next foundation layer for enterprise AI.

As a Research Scientist at Skyfall, you will help advance the state of the art in world modeling. You will design and develop novel methods for:

• Causal reasoning
• Long-horizon planning
• Continual learning and rapid adaptation
• Active learning via experimentation
• Abstraction of state, action, and dynamics
• Counterfactual inference

Your work will directly contribute to building scalable, world models capable of robust decision-making in complex, dynamic environments.

We are looking for deeply creative researchers who are excited about tackling open problems at the intersection of:

• Program synthesis
• Multi-modal reasoning
• Graph-based reasoning

• Develop novel algorithms and research directions in world modeling, planning, and reasoning
• Design rigorous experiments and demonstrate measurable improvements in complex environments
• Collaborate closely with a small, high-caliber research team
• Publish and communicate research insights internally and externally
• Stay at the forefront of advancements in LLMs, reinforcement learning, multi-agent systems, and reasoning architectures

• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field or
• Master’s degree with 5+ years of industry research experience
• Demonstrated experience working with large models (LLMs, foundation models, or world models)
• Strong programming skills in Python
• Experience with modern deep learning frameworks (e.g., PyTorch, Tensor Flow)
• Proven research track record (publications at top venues or equivalent demonstrated impact)

• Research in planning or long-horizon decision-making, particularly model-based approaches
• Experience developing world models or simulation-based learning systems
• Experience in rapid adaptation and data-efficient learning
• Expertise in reasoning with LLMs
• Background in causal modeling or structural learning