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Senior AI Research Scientist - AGI & Future Tech

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Join the Architects of the Future.

Nexus Horizon Labs is seeking a visionary Senior AI Research Scientist to lead our breakthrough initiatives in Artificial General Intelligence (AGI). As we look toward 2026 and beyond, we are building the foundational models that will redefine human-machine interaction. This is not just a job; it is an opportunity to shape the trajectory of technology for the next decade.

You will work in a high-performance environment, pushing the boundaries of deep learning, neural architecture search, and emergent behavior simulation. If you are obsessed with the possibilities of 2026 and want to build the systems that will define it, we want to hear from you.

Responsibilities

  • Lead AGI R&D: Spearhead research projects focused on achieving Artificial General Intelligence, including reasoning, planning, and multi-modal learning.
  • Model Optimization: Architect and optimize large-scale neural networks for speed, accuracy, and efficiency on next-gen hardware.
  • Technical Strategy: Define the technical roadmap for future-proofing our AI infrastructure to support 2026 market demands.
  • Collaboration: Partner with engineering and product teams to translate theoretical research into deployable, scalable software solutions.
  • Mentorship: Guide junior researchers and engineers, fostering a culture of innovation and continuous learning.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on AI, Machine Learning, or Cognitive Science.
  • Experience: 5+ years of professional experience in research engineering or applied machine learning, with at least 2 years in a leadership role.
  • Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Ray, Spark).
  • Domain Knowledge: Deep understanding of transformer architectures, LLMs, or reinforcement learning.
  • Creativity: Demonstrated ability to think abstractly and solve complex, open-ended problems.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Distributed Systems Research Engineering

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