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AI Research Scientist - 2026 Visionary

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking an AI Research Scientist to architect transformative systems that will redefine human-computer interaction. In this role, you'll collaborate with Nobel laureates and MIT-affiliated researchers to develop quantum-resistant neural networks and next-generation generative AI frameworks. Our state-of-the-art facility in downtown San Francisco offers unparalleled resources for breakthrough innovation.

What you'll achieve:
• Lead research initiatives with global impact
• Publish findings in top-tier journals
• Mentor the next generation of AI pioneers
• Shape ethical AI standards for 2026+

Responsibilities

  • Design and implement cutting-edge AI architectures for future-facing applications
  • Lead cross-functional research teams in developing quantum-secure machine learning models
  • Publish 3+ peer-reviewed papers annually in AI/ML conferences
  • Collaborate with product teams to translate research into commercial solutions
  • Establish ethical frameworks for autonomous systems deployment
  • Develop novel approaches to explainable AI and bias mitigation
  • Secure $2M+ in research funding through NSF and DARPA proposals

Qualifications

  • PhD in Computer Science, AI, or related field (or equivalent experience)
  • 5+ years in applied AI research with publications at NeurIPS/ICML
  • Expertise in transformer architectures and generative models
  • Proficiency in PyTorch/TensorFlow and distributed computing
  • Experience with quantum computing frameworks (Qiskit, Cirq)
  • Strong background in differential privacy and federated learning
  • Demonstrated ability to lead research initiatives from concept to production
  • Published work in AI ethics or responsible AI preferred

Required Skills

Artificial Intelligence Machine Learning Quantum Computing Neural Networks PyTorch TensorFlow Research Ethics Generative AI Distributed Systems

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