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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer breakthroughs that will redefine humanity's future. We're seeking an exceptional AI Research Scientist to architect next-generation systems that will power the world of 2026 and beyond. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art facility overlooking the Bay, where every idea fuels innovation.

We offer unparalleled resources, flexible work arrangements, and a culture that celebrates intellectual curiosity. Your work will directly impact global industries while shaping ethical AI frameworks for tomorrow's challenges.

Responsibilities

  • Design and implement novel machine learning architectures for autonomous systems
  • Lead cross-functional teams in developing quantum-encrypted neural networks
  • Publish breakthrough research in top-tier AI journals and conferences
  • Translate theoretical models into scalable production solutions
  • Mentor junior researchers and foster collaborative innovation
  • Develop ethical AI frameworks aligned with 2026 regulatory standards
  • Secure $5M+ in research grants through compelling proposal development

Qualifications

  • PhD in Computer Science, Machine Learning, or related field (or equivalent experience)
  • 5+ years developing production-level AI systems with measurable impact
  • Published research in NeurIPS, ICML, or equivalent tier-1 conferences
  • Expertise in transformer architectures, reinforcement learning, and federated systems
  • Proficiency in PyTorch/TensorFlow and distributed computing frameworks
  • Demonstrated ability to lead complex technical projects from concept to deployment
  • Strong background in AI ethics and responsible development practices

Required Skills

Machine Learning Deep Learning PyTorch TensorFlow Quantum Computing Neural Networks Reinforcement Learning Distributed Systems AI Ethics

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