Principal AI/ML Researcher
Core
Architecting and operationalizing cognitive AI systems that combine post-trained foundational models, explicit memory, and recursive planning strategies for real-world decisioning.
Role type
Principal AI/ML Researcher (Reasoning, Planning, and Decision-Making)
Builds
Intelligent decisioning substrates, multi-agent systems, and cognitive AI architectures for personalized environments.
Domain
AI/ML, Cognitive Systems, Reasoning, Planning, Reinforcement Learning
Deliverable
production ML models
Required skills
Post-training intelligence frameworks, Large Reasoning Models (LRMs), Knowledge Graphs, Reinforcement Learning, Multi-agent systems, Symbolic-sub-symbolic integration, Distributed reasoning, Plan induction, Value estimation, Hybrid model architectures (connectionist-symbolic), Multi-agent coordination
Preferred skills
Ph.D. in AI/ML/Robotics, Published work/patents in multi-agent reasoning, Neuro-symbolic systems, Memory architectures, Task graphs, Semantic program induction
Technologies
Java, Python, C++, PyTorch, Ray, JAX, RLlib
Responsibilities
Drive foundational research in reasoning engines and planning architectures; Architect RPD systems integrating LLMs/LRMs, KGs, and RL controllers; Build stateful dynamic models combining supervised learning and reinforcement; Set technical direction for planning infrastructure; Mentor teams in systems thinking and causal modeling; Productionize real-time reasoning loops with low-latency inference.
Seniority
Principal, hands-on IC with strategic influence
