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Senior AI Research Scientist - AGI Architect

Nexus Horizon Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

We are seeking a visionary leader to join our elite AI division focused on defining the roadmap for 2026 and beyond. At Nexus Horizon, we are not just building software; we are architecting the intelligence that will power the next generation of human-machine interaction. If you are passionate about the theoretical limits of Artificial General Intelligence (AGI) and want to apply your expertise to solve the world's most complex problems, we want to hear from you.

As a Senior AI Research Scientist, you will spearhead the development of next-generation foundation models, pushing the boundaries of what is possible in reasoning, multi-modal understanding, and autonomous learning systems.

Responsibilities

  • Design and implement novel deep learning architectures capable of scaling to trillions of parameters.
  • Lead high-impact research initiatives aimed at achieving artificial general intelligence (AGI) milestones.
  • Optimize model training pipelines for efficiency, targeting a 40% reduction in inference costs.
  • Collaborate cross-functionally with engineering, product, and design teams to translate theoretical research into production-ready systems.
  • Publish cutting-edge papers at top-tier conferences (NeurIPS, ICML, ICLR) and actively contribute to the open-source community.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field with a focus on AI/ML.
  • Minimum of 5 years of experience in research or applied machine learning, preferably at a top-tier tech company or AI lab.
  • Deep expertise in deep learning frameworks such as PyTorch or TensorFlow.
  • Strong background in Natural Language Processing (NLP) or Reinforcement Learning.
  • Proven ability to lead a research team and mentor junior scientists.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Reinforcement Learning Research Distributed Systems Big Data

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