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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
23 Mei 2026
Deadline
23 Mei 2027

Job Description

Join Nexus Labs at the forefront of 2026's technological revolution. We're pioneering next-generation AI systems that will redefine human-machine interaction. As a key member of our research team, you'll architect breakthrough solutions in neural networks and autonomous systems while collaborating with Nobel laureates and Turing Award winners. Our state-of-the-art Silicon Valley campus offers unparalleled resources for innovation, including quantum computing clusters and real-world deployment environments.

We provide comprehensive benefits including equity, unlimited PTO, and a $20,000 annual education stipend. Shape the future with us.

Responsibilities

  • Lead R&D initiatives for 2026-era AI architectures (quantum neural networks, neuromorphic computing)
  • Develop novel algorithms for multimodal generative AI systems
  • Collaborate with cross-functional teams to prototype AI applications in healthcare, climate science, and space exploration
  • Publish breakthrough research in top-tier AI conferences (NeurIPS, ICML)
  • Mentor junior researchers and contribute to open-source AI frameworks
  • Secure $5M+ in government/private research grants for 2026 initiatives

Qualifications

  • PhD in Computer Science, AI, or related field (or equivalent industry breakthroughs)
  • 5+ years developing production-level AI systems with 10M+ user impact
  • Expertise in transformer architectures, reinforcement learning, and generative models
  • Published research at NeurIPS/ICML/AAAI with 500+ citations
  • Proficiency in PyTorch/TensorFlow and distributed ML frameworks
  • Experience with quantum computing APIs (Qiskit, Cirq) preferred
  • Portfolio demonstrating 2026-relevant innovations (autonomous agents, AGI prototypes)

Required Skills

Machine Learning Deep Learning Python TensorFlow PyTorch Quantum Computing Neural Networks Generative AI Reinforcement Learning

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