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AI Research Scientist

Nexus Dynamics Inc.
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join Nexus Dynamics Inc., a trailblazer in quantum computing and AI innovation, as we redefine technological boundaries in 2026. We seek visionary AI Research Scientists to architect next-generation machine learning models that will power autonomous systems, biotech breakthroughs, and sustainable energy solutions. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art Silicon Valley campus, equipped with $50M+ in R&D infrastructure. Your work will directly impact Fortune 500 partners and shape the future of human-computer interaction.

What you'll achieve: Pioneering research in generative AI, neural architecture optimization, and cross-modal learning systems. Publication in top-tier journals (NeurIPS, ICML) and patent development for proprietary algorithms. Mentorship opportunities for junior researchers and participation in global tech summits.

Responsibilities

  • Design and implement novel deep learning architectures for real-time predictive analytics
  • Lead cross-functional projects integrating AI with IoT and blockchain ecosystems
  • Develop ethical AI frameworks ensuring compliance with emerging global regulations
  • Optimize computational efficiency for edge deployment in autonomous vehicles and medical devices
  • Collaborate with quantum computing teams to hybridize classical and quantum AI models
  • Present research findings at industry conferences and publish in peer-reviewed journals
  • Mentor junior researchers and contribute to open-source AI initiatives

Qualifications

  • PhD in Computer Science, Machine Learning, or related field with 3+ years industry experience
  • Expertise in PyTorch/TensorFlow, distributed computing (Spark/Kubernetes), and MLOps
  • Published record in top-tier AI conferences with 5+ peer-reviewed papers
  • Proficiency in Python, CUDA, and low-level optimization techniques
  • Experience with large-scale LLM fine-tuning and RLHF methodologies
  • Demonstrated understanding of AI ethics, bias mitigation, and responsible AI practices
  • Strong background in at least one specialized domain: computer vision, NLP, or reinforcement learning

Required Skills

Machine Learning Deep Learning PyTorch TensorFlow Quantum Computing MLOps LLMs Computer Vision NLP Distributed Computing AI Ethics

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