Principal AI/ML Researcher / Engineer Reasoning, Planning, and Decision-making systems
Tasks
- Apply reinforcement learning to adaptive decisioning
- Architect planning and decision making systems
- Build belief state trackers
- Combine supervised learning with online offline reinforcement
- Define coordination and communication protocols
- Deploy Retrieval-Augmented Generation pipelines
- Design recursive task planners
- Develop stateful dynamic hybrid models
- Drive research in reasoning engines
- Implement monitoring attribution and evaluation for agents
- Implement multi agent reasoning systems
- Integrate large language models with knowledge graphs
- Operationalize multi agent orchestration fault tolerant communication
- Optimize adaptive exploration and planning horizon control
- Productionize real time reasoning loops
- Set direction for planning reasoning infrastructure
Perks/Benefits
- N/A
Skills/Tech-stack
Agent systems | Belief State Tracking | C++ | Decision Making | Distributed Reinforcement Learning | Graph inference | JAX | Java | Knowledge graphs | LLM post training | Language Models | Large Language Models | Machine Learning | Multi-Agent | Multi-Agent Systems | Neuro-Symbolic | Planning | Post-training | PyTorch | Python | Ray | Recursive Task Planning | Reinforcement Learning | Retrieval-Augmented Generation | Rllib | Simulation | State tracking | Task planning
Education
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