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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist (2026)

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We seek an AI Research Scientist to develop transformative machine learning models that will shape the future of human-computer interaction. This role offers unparalleled opportunities to work with quantum computing interfaces, generative AI frameworks, and predictive analytics systems in a collaborative, innovation-driven environment. Your work will directly impact industries from healthcare to autonomous systems, positioning you as a key architect of tomorrow's digital landscape.

Responsibilities

  • Design and implement advanced neural network architectures for next-generation AI systems
  • Lead research initiatives in quantum machine learning and generative AI models
  • Collaborate with cross-functional teams to deploy AI solutions in production environments
  • Publish groundbreaking research in peer-reviewed journals and industry conferences
  • Develop ethical AI frameworks ensuring responsible deployment of autonomous systems
  • Mentor junior researchers and foster a culture of scientific excellence

Qualifications

  • PhD in Computer Science, Machine Learning, or related field with 3+ years industry experience
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Proficiency in Python, TensorFlow/PyTorch, and distributed computing frameworks
  • Published record in top-tier AI/ML conferences (NeurIPS, ICML, CVPR)
  • Strong background in ethical AI development and bias mitigation techniques
  • Experience with cloud platforms (AWS/Azure) and MLOps pipelines
  • Proven ability to translate complex research into scalable commercial applications

Required Skills

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

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