Job Description
Join NeuraForge Labs at the forefront of AI innovation as we build transformative systems for 2026 and beyond. We're seeking a visionary Research Scientist to pioneer next-generation neural architectures and quantum-entangled machine learning models. Our multidisciplinary team operates at the intersection of computational neuroscience, synthetic data generation, and ethical AI governance. You'll lead breakthrough projects in autonomous reasoning systems and adaptive human-AI symbiosis while contributing to our open-source initiatives that democratize advanced AI capabilities.
This role offers unparalleled resourcesâincluding our 10,000-qubit quantum simulation clusterâand collaboration with Nobel laureate advisors. We provide competitive equity packages, flexible hybrid work arrangements, and dedicated R&D time for your moonshot projects. Shape the future of intelligence.
Responsibilities
- Design and implement novel deep learning architectures for 2026-era autonomous systems
- Lead research in quantum-enhanced neural networks and probabilistic reasoning
- Develop ethical frameworks for AI decision-making transparency and bias mitigation
- Collaborate with robotics teams to deploy AI models in physical environments
- Author peer-reviewed publications and contribute to open-source AI repositories
- Mentor junior researchers and present findings at global AI summits
- Secure research grants and partnerships with leading academic institutions
Qualifications
- PhD in Machine Learning, Computer Science, or Computational Neuroscience (or equivalent experience)
- 5+ years of experience in neural network research with 3+ publications at NeurIPS/ICML
- Expertise in transformer architectures, diffusion models, and reinforcement learning
- Proficiency with quantum computing frameworks (Qiskit, Cirq) and HPC environments
- Strong background in causal inference and explainable AI methodologies
- Experience leading cross-functional technical teams from ideation to deployment
- Demonstrated ability to translate theoretical research into production-ready systems
- Portfolio of open-source contributions (GitHub with 5k+ stars preferred)