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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Research Scientist - 2026 Vision

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Labs at the forefront of 2026's technological revolution. We're seeking an exceptional AI/ML Research Scientist to pioneer breakthroughs in quantum-resistant algorithms and neural-symbolic integration. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art San Francisco lab, developing the next generation of autonomous systems that will redefine human-computer interaction.

Our team operates at the intersection of quantum computing and ethical AI, with projects ranging from real-time climate modeling to personalized healthcare diagnostics. You'll leverage our $50M research fund and access to quantum processors to tackle humanity's most pressing challenges.

Responsibilities

  • Design and implement novel neural-symbolic architectures for explainable AI systems
  • Lead research in post-quantum cryptography and zero-knowledge proofs
  • Develop adaptive learning algorithms for edge-computing environments
  • Collaborate with cross-functional teams to prototype production-ready AI solutions
  • Publish findings in top-tier journals and present at global conferences
  • Mentor junior researchers and foster innovation through hackathons

Qualifications

  • PhD in Computer Science, Mathematics, or related field with 5+ years research experience
  • Expertise in transformer architectures and reinforcement learning
  • Published work in NeurIPS/ICML/ICLR or equivalent tier conferences
  • Proficiency in PyTorch/TensorFlow and quantum programming frameworks
  • Strong background in differential privacy and federated learning
  • Demonstrated ability to translate research into commercial applications
  • Experience with high-performance computing and distributed systems

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks Cryptography Python PyTorch TensorFlow Differential Privacy

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