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AI Research Scientist (2026)

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of 2026's technological revolution. We're pioneering quantum-AI hybrid systems that will redefine human-machine collaboration. As an AI Research Scientist, you'll architect breakthrough solutions in autonomous reasoning, generative intelligence, and ethical AI governance. Our interdisciplinary team works in state-of-the-art labs with unparalleled computational resources, including quantum annealing processors and exascale supercomputing. This role offers unparalleled autonomy to explore uncharted territories of machine cognition while contributing to frameworks that will shape global AI policy.

Responsibilities

  • Lead research initiatives in next-generation neural architectures for 2026-era applications
  • Develop novel algorithms for autonomous decision-making systems with ethical safeguards
  • Collaborate with quantum computing teams to hybridize classical and quantum AI models
  • Author peer-reviewed publications and patents for transformative AI methodologies
  • Design scalable frameworks for real-time generative intelligence at industrial scale
  • Advise on AI ethics and governance frameworks for global regulatory bodies
  • Mentor cross-functional teams in advanced ML implementation strategies

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years industry research
  • Expertise in transformer architectures, reinforcement learning, and generative models
  • Published work in top-tier AI/ML conferences (NeurIPS, ICML, ICLR)
  • Proficiency with PyTorch/TensorFlow and distributed computing frameworks
  • Experience with quantum machine learning algorithms and hybrid systems
  • Strong background in AI ethics, fairness metrics, and bias mitigation
  • Demonstrated ability to translate research into production-scale solutions

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks PyTorch TensorFlow Reinforcement Learning Generative AI AI Ethics

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