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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist (2026 Vision)

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

Job Description

Join Nexus Labs at the forefront of 2026's technological revolution. We're pioneering AI systems that will redefine industries, and we need visionary researchers to architect the future. As an AI Research Scientist, you'll work in our state-of-the-art San Francisco lab, collaborating with Nobel laureates and Turing Award winners to develop breakthrough neural networks and quantum-optimized algorithms.

We offer unparalleled resources: dedicated quantum computing clusters, petabyte-scale datasets, and a culture where 20% of time is reserved for moonshot projects. Our benefits include equity grants, unlimited learning stipends, and sabbaticals for deep-dive research.

Responsibilities

  • Design and implement novel deep learning architectures for next-generation autonomous systems
  • Lead cross-functional teams to integrate AI solutions into production environments
  • Publish breakthrough research in top-tier journals (Nature, Science, NeurIPS)
  • Develop ethical frameworks for bias mitigation in large-scale AI deployments
  • Secure $5M+ in government/private research grants for 2026 initiatives
  • Mentor PhD candidates in our 'Future Minds' internship program

Qualifications

  • PhD in Computer Science, AI, or Quantum Computing (or equivalent research experience)
  • 5+ years of applied ML research with peer-reviewed publications
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Proficiency in PyTorch/TensorFlow and distributed computing frameworks
  • Track record of shipping production AI systems at scale
  • Deep understanding of quantum computing principles (Qiskit experience preferred)
  • Passion for solving problems that impact humanity by 2026

Required Skills

AI Research Machine Learning Deep Learning Quantum Computing PyTorch TensorFlow Reinforcement Learning Transformers Distributed Systems

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