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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist (2026 Vision)

NeuroEdge Dynamics
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join NeuroEdge Dynamics at the forefront of 2026's AI revolution. We're pioneering quantum neural networks and autonomous cognitive systems that will redefine human-machine collaboration. As our AI Research Scientist, you'll architect breakthrough algorithms in generative AI and ethical machine learning, working with Fortune 500 partners to deploy solutions that solve humanity's most complex challenges. Your innovations will power the next generation of intelligent automation, predictive analytics, and adaptive AI systems that will shape the technological landscape of the mid-2020s.

Responsibilities

  • Design and implement novel deep learning architectures for generative AI systems
  • Lead cross-functional teams in developing quantum-optimized neural networks
  • Publish groundbreaking research in top-tier AI conferences (NeurIPS, ICML, ICLR)
  • Develop ethical AI frameworks for bias mitigation and transparency
  • Collaborate with product teams to translate research into production-ready solutions
  • Drive innovation in federated learning and differential privacy techniques
  • Mentor junior researchers and establish new industry benchmarks

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years industry experience
  • Expertise in PyTorch/TensorFlow and distributed computing frameworks
  • Published record in top-tier AI conferences (NeurIPS, ICML, ICLR)
  • Strong background in reinforcement learning and generative adversarial networks
  • Experience deploying AI systems at scale (AWS/GCP/Azure)
  • Proficiency in MLOps and CI/CD for AI workflows
  • Demonstrated ability to translate complex research into practical applications

Required Skills

AI Research Deep Learning Quantum Computing Generative AI Machine Learning PyTorch TensorFlow Reinforcement Learning MLOps

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