Principal AI/ML Researcher / Engineer In Reasoning, Planning, and Decision-making systems

15+ years in AI/ML, including post-training architectures and production-scale reasoning systems.

Advanced coding proficiency in Java, Python, C++, or similar, with experience in ML/RL frameworks (e.g., PyTorch, Ray, JAX, RLlib) at scale.

Proven experience integrating LLMs/LRMs with Knowledge Graphs or structured world models.

Fluency in hybrid model architectures: connectionist-symbolic fusion, retrieval-based agents, or goal-directed transformers.

Experience working on multi-agent coordination, distributed RL, or cooperative inference systems.

Published work or patents in multi-agent reasoning, plan synthesis, knowledge-augmented learning, or generative control.

You will be responsible for inventing, scaling, and operationalizing intelligent decisioning substrates that blend symbolic and sub-symbolic methods, enabling next-generation AI systems that go beyond pattern recognition into the realm of deliberation, foresight, and agency.

Our mission is to build cognitive AI systems that combine post-trained foundational models, explicit memory and knowledge, and recursive planning strategies to power sophisticated real-world decisioning in personalized environments.

You will collaborate across disciplines and influence company-wide AI architecture.

A core dimension of this role is the design and deployment of multi-agent systems, where reasoning, planning, and decisioning are distributed across networks of intelligent agents.

You will formulate coherent, synergistic strategies that enable agents to cooperate, negotiate, and align objectives, ensuring that distributed intelligence converges to purposeful, high-quality outcomes across contexts.