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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
New
Live Update
7 Juli 2026
Deadline
7 Jul 2027

Job Description

Join Nexus Labs at the forefront of 2026's AI revolution. We're pioneering breakthroughs in quantum neural networks and autonomous systems that will redefine human-computer interaction. As an AI Research Scientist, you'll shape the future by developing next-generation algorithms that power our flagship 'Project Horizon' initiative. Collaborate with Nobel laureates and industry disruptors in our state-of-the-art research facility overlooking the San Francisco Bay.

We offer unparalleled resources, flexible work arrangements, and equity participation in our moonshot projects. Your work will directly impact how billions interact with technology in the coming decade.

Responsibilities

  • Design and implement novel AI architectures for 2026-era autonomous systems
  • Lead cross-functional research teams in quantum machine learning development
  • Publish groundbreaking findings in top-tier journals and conferences
  • Translate theoretical models into production-ready prototypes with 99.99% reliability
  • Collaborate with ethics committees to ensure responsible AI deployment
  • Secure $2M+ in annual research funding through grant proposals
  • Mentor PhD candidates and postdoctoral researchers

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Published research in NeurIPS/ICML/ICLR with 100+ citations
  • Expertise in transformer architectures, reinforcement learning, and causal inference
  • Proficiency in PyTorch, TensorFlow Quantum, and high-performance computing
  • Track record of shipping production-level AI systems at scale
  • Deep understanding of 2026's regulatory landscape for autonomous systems
  • Exceptional problem-solving skills for NP-hard optimization challenges

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks Python PyTorch TensorFlow Reinforcement Learning Causal Inference High-Performance Computing

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