Research at the frontier
of machine intelligence
Our research program operates at the intersection of fundamental science and systems engineering. Every research direction is chosen for its potential to compound into durable capability.
Where we invest
Model Architecture
ActiveDesigning novel architectures that improve capability scaling, training efficiency, and inference performance. Our work spans attention mechanisms, mixture-of-experts routing, and efficient tokenization strategies.
Alignment & Safety
ActiveEnsuring that increasingly capable systems remain predictable, controllable, and aligned with specified objectives. We invest in interpretability, red-teaming, and formal verification approaches.
Reasoning & Planning
ActiveDeveloping systems with improved multi-step reasoning, logical consistency, and long-horizon planning capabilities. Our work integrates symbolic methods with learned representations.
Multimodal Learning
ActiveBuilding unified architectures that process and reason across text, images, audio, and structured data. We focus on emergent cross-modal capabilities and grounded understanding.
Systems & Infrastructure
ActiveOptimizing the full training and serving stack—from distributed training frameworks and custom kernels to inference optimization and hardware-software co-design.
Applied Intelligence
PlannedTranslating fundamental research into production systems for enterprise applications, scientific discovery, and institutional decision-making.
Current initiatives
Selected projects from our active research program.
Efficient Long-Context Reasoning
Investigating architectural innovations that enable models to reason coherently over documents and codebases exceeding 100K tokens without degradation in retrieval accuracy or logical consistency.
Verifiable Alignment Framework
Developing a principled approach to specifying, testing, and certifying model behavior against formal behavioral contracts—moving alignment from heuristic evaluation toward engineering discipline.
Distributed Training at Frontier Scale
Building custom training infrastructure that maximizes compute utilization across heterogeneous hardware configurations while maintaining numerical stability and reproducibility.
Structured Code Intelligence
Training specialized models for deep code understanding—spanning program synthesis, automated debugging, and formal verification of software systems.
Join our research team
We are looking for research scientists, engineers, and technical leaders who want to work on problems of genuine consequence.