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Senior AI Research Engineer - 2026 Vision

NeuroSync Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join NeuroSync Technologies at the forefront of cognitive AI development for our 2026 flagship project. We're pioneering next-generation neural interfaces that will redefine human-machine collaboration. As a Senior AI Research Engineer, you'll architect breakthrough solutions in adaptive machine learning and neuro-symbolic systems. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical concepts into revolutionary applications.

What You'll Achieve:
You'll lead the development of autonomous reasoning systems capable of contextual understanding beyond current LLM capabilities. Your work will directly influence the deployment of ethical AI frameworks in healthcare diagnostics and autonomous decision-making platforms. We provide competitive equity, flexible R&D budgets, and collaboration with Nobel laureate advisors.

Responsibilities

  • Design and implement novel neural architectures for contextual reasoning
  • Lead cross-functional teams in deploying AI prototypes for 2026 healthcare initiatives
  • Develop neuro-symbolic integration frameworks for explainable AI
  • Optimize multimodal learning systems using advanced transformer architectures
  • Drive ethical AI governance protocols for autonomous systems
  • Publish research in top-tier AI/ML conferences
  • Mentor junior engineers in cutting-edge AI methodologies

Qualifications

  • PhD in Machine Learning, Cognitive Science, or related field with 5+ years industry experience
  • Expertise in PyTorch/TensorFlow with 100M+ parameter model deployment
  • Proven track record in neuro-symbolic AI research
  • Published research at NeurIPS, ICML, or equivalent tier-1 venues
  • Strong background in ethical AI frameworks and bias mitigation
  • Experience with multimodal learning architectures (vision, language, sensor fusion)
  • Proficiency in high-performance computing environments (CUDA, distributed training)

Required Skills

PyTorch TensorFlow Neuro-Symbolic AI Multimodal Learning Ethical AI Distributed Training CUDA Reinforcement Learning

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