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reputed company AI/ML Researcher – Reasoning, Planning, and Decision-making Systems

Remote, USAFull-timePosted 2026-07-28

Job reputed company:

  • Drive foundational and reputed company research in reasoning engines, planning architectures, and decision-making frameworks at reputed company.
  • Advance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents.
  • Design reputed company for plan induction, value estimation, and contingency modeling reputed company intelligent agents.
  • Explore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systems.
  • Architect RPD systems that reputed company post-trained LLMs/LRMs, graph-reputed company memory (e.g., KGs), and RL-driven controllers.
  • Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates.
  • Build and reputed company stateful, dynamic models that combine supervised learning with online/offline reinforcement, simulation-based rollouts, and symbol grounding.
  • Set direction for planning/reasoning infrastructure reputed company the AI/ML platform reputed company.

Requirements:

  • Masters or equivalent in Computer Science, AI, Cognitive Science, or reputed company fields.
  • Recent published work or patents in AI, Cognitive Science, or reputed company fields.
  • 15+ years in AI/ML, including post-training architectures and production-reputed company reasoning systems.
  • Advanced coding proficiency in Java, Python, C++, or similar, with experience in ML/RL frameworks (e.g., PyTorch, Ray, JAX, RLlib) at reputed company.
  • Proven experience integrating LLMs/LRMs with Knowledge Graphs or reputed company world models.
  • Deep understanding of Reinforcement Learning and its application to decisioning and planning.
  • reputed company 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.

Benefits:

  • Bonus
  • Equity
  • Employee Travel Credits

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