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AI Research Scientist

  • AI Research Scientist job type Posted on: Nov 02, 2026
  • AI Research Scientist experience level Noetive
  • AI Research Scientist employment type Remote, Remote
  • AI Research Scientist employment type Remote
  • AI Research Scientist salary Full-time

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Job Title :

AI Research Scientist

Job Type :

Full-Time

Job Location :

Remote Remote United States

Remote :

Yes

Jobcon Logo Job Description :

Company Description Noetive is a research lab building recursive self-improvement to develop intelligence for the physical economy.Role Description At Noetive, you'll push the frontier of what foundation models can do across language, vision, and world model development, designing and running experiments on pre and post-training, reasoning, agentic behavior, and evaluation, then translating those findings into capabilities that ship in real products. You'll work with a small, principal-level team that moves fast from hypothesis to result, own the full arc from literature review through ablations to writeup, and hold a high bar for rigor even under startup timelines. We're looking for a PhD or equivalent research track record, deep fluency in modern deep learning (PyTorch, distributed training, LLM fine-tuning and RL), a strong publication or open-source footprint, and the instinct to pick problems that matter rather than problems that are merely publishable.

Jobcon Logo Position Details

Posted:

Nov 02, 2026

Reference Number:

10440_4481162915

Employment:

Full-time

City:

Remote

Job Origin:

APPCAST_CPC

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Company Description Noetive is a research lab building recursive self-improvement to develop intelligence for the physical economy.Role Description At Noetive, you'll push the frontier of what foundation models can do across language, vision, and world model development, designing and running experiments on pre and post-training, reasoning, agentic behavior, and evaluation, then translating those findings into capabilities that ship in real products. You'll work with a small, principal-level team that moves fast from hypothesis to result, own the full arc from literature review through ablations to writeup, and hold a high bar for rigor even under startup timelines. We're looking for a PhD or equivalent research track record, deep fluency in modern deep learning (PyTorch, distributed training, LLM fine-tuning and RL), a strong publication or open-source footprint, and the instinct to pick problems that matter rather than problems that are merely publishable.

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