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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Engineer

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join Nexus Innovations at the forefront of 2026's technological revolution! We're seeking visionary AI Research Engineers to pioneer next-generation artificial intelligence solutions that will redefine human-machine interaction. Collaborate with Nobel laureates and Silicon Valley pioneers in our state-of-the-art R&D facility, where your work directly impacts autonomous systems, quantum computing interfaces, and ethical AI frameworks. Enjoy competitive equity packages, flexible work arrangements, and unparalleled professional development in a culture that celebrates disruptive innovation.

Responsibilities

  • Design and implement novel deep learning architectures for autonomous decision-making systems
  • Lead cross-functional research projects integrating quantum computing with classical AI models
  • Develop ethical AI frameworks ensuring compliance with 2026 global AI governance standards
  • Collaborate with product teams to translate research breakthroughs into commercial applications
  • Publish findings in top-tier journals and present at international AI symposiums
  • Mentor junior researchers and contribute to patent development portfolios

Qualifications

  • PhD or equivalent in Computer Science, Machine Learning, or related field with 3+ years industry experience
  • Proven expertise in transformer architectures, reinforcement learning, and multimodal AI systems
  • Publication record in NeurIPS, ICML, or equivalent tier conferences
  • Strong proficiency in PyTorch/TensorFlow and distributed computing frameworks
  • Experience with MLOps pipelines and cloud-based AI deployment (AWS/GCP/Azure)
  • Demonstrated ability to translate theoretical research into scalable production systems
  • Understanding of quantum computing principles and their AI applications

Required Skills

Deep Learning Reinforcement Learning Quantum Computing PyTorch AI Ethics MLOps Multimodal AI

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