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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist - 2026 Vision

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Innovations at the forefront of 2026's AI revolution! We're seeking visionary AI Research Scientists to architect the next generation of intelligent systems that will redefine human-machine interaction. Our cross-disciplinary teams work on groundbreaking projects in generative AI, autonomous systems, and quantum-enhanced machine learning. You'll collaborate with Nobel laureates and industry pioneers in our state-of-the-art labs, publishing research that shapes global AI policy while building products used by millions.

What You'll Achieve: Design novel neural architectures, publish at NeurIPS/ICML, and translate theoretical breakthroughs into production-ready solutions. Your work will directly impact healthcare diagnostics, climate modeling, and personalized education systems.

Responsibilities

  • Lead R&D initiatives in next-gen AI paradigms (AGI, neuromorphic computing)
  • Develop novel algorithms for multimodal understanding across 10M+ parameter models
  • Collaborate with quantum computing teams to pioneer hybrid AI systems
  • Author 3+ peer-reviewed publications annually in top-tier venues
  • Translate research into scalable solutions serving 50M+ users
  • Mentor PhD researchers and patent breakthrough methodologies

Qualifications

  • PhD in Computer Science, AI, or related field (or equivalent research impact)
  • 5+ years of experience in deep learning framework development
  • Published work at NeurIPS/ICML/ICLR with 200+ citations
  • Expertise in transformer architectures and diffusion models
  • Proficiency in PyTorch/TensorFlow and distributed training
  • Strong background in ethics and responsible AI frameworks
  • Experience with MLOps at enterprise scale

Required Skills

AI Research Deep Learning Machine Learning Neural Networks PyTorch TensorFlow Quantum Computing Generative AI Multimodal Systems MLOps

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