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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist 2026

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

Job Description

Join Nexus Dynamics at the forefront of technological evolution as we pioneer breakthrough AI systems for 2026. We're seeking visionary AI Research Scientists to architect next-generation machine learning frameworks that will redefine industries. Work alongside Nobel laureates and Turing Award winners in our state-of-the-art Silicon Valley lab, where your innovations will directly shape humanity's digital future.

This role offers unparalleled resources for ambitious researchers: unlimited cloud computing credits, dedicated prototyping budgets, and collaboration with Fortune 500 partners. Your work will focus on developing ethical, scalable AI solutions for climate modeling, personalized medicine, and autonomous systems.

Responsibilities

  • Design and implement novel deep learning architectures for 2026-era applications
  • Lead cross-functional teams to translate theoretical models into production-ready systems
  • Publish breakthrough research in top-tier AI journals and conferences
  • Develop ethical frameworks for autonomous decision-making systems
  • Collaborate with quantum computing teams to hybridize classical-quantum AI models
  • Mentor junior researchers and foster innovation through internal hackathons

Qualifications

  • PhD in Computer Science, Machine Learning, or related field (or equivalent industry experience)
  • 5+ years of experience in developing production-level AI systems
  • Published research in NeurIPS, ICML, or equivalent tier-1 venues
  • Expertise in transformer architectures, reinforcement learning, and multimodal systems
  • Proficiency in PyTorch/TensorFlow and distributed computing frameworks
  • Demonstrated ability to translate academic research into commercial applications
  • Strong background in AI ethics and responsible development practices

Required Skills

Deep Learning Reinforcement Learning Transformer Models Quantum Computing Ethics PyTorch Multimodal AI Distributed Systems AI Safety

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