Job Description
We are at the forefront of the 2026 Initiative, a groundbreaking research program dedicated to defining the next era of Artificial General Intelligence (AGI). We are seeking a visionary Senior AI Research Engineer to architect the neural foundations that will power the future of human-machine symbiosis.
In this role, you will move beyond standard machine learning to pioneer adaptive, self-evolving systems. You will collaborate with world-class neuroscientists and engineers to build models capable of reasoning, creativity, and autonomous learning at a superhuman scale.
Why Join Us?
- Work on projects with a 5-year horizon (2026 vision).
- Access to proprietary quantum computing resources.
- Competitive equity package and top-tier benefits.
Responsibilities
- Lead Research Architecture: Design and implement next-generation transformer architectures and multi-modal learning models.
- Model Optimization: Optimize large-scale neural networks for real-time inference on edge devices and quantum processors.
- Publish & Patent: Author peer-reviewed papers and file patents for novel AI methodologies.
- Cross-Functional Leadership: Mentor junior researchers and bridge the gap between theoretical CS and practical engineering.
- Ethical AI Governance: Ensure all 2026 system outputs adhere to strict safety and ethical alignment protocols.
- Simulation & Testing: Build rigorous testbeds to simulate AI behavior in complex, unpredictable environments.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of industry experience in deep learning, specifically with PyTorch or TensorFlow.
- Technical Skills: Proficiency in distributed computing (Ray, Kubernetes) and high-performance computing (CUDA).
- Research Track Record: Demonstrated history of publishing in top-tier conferences (NeurIPS, ICML, ICLR).
- Programming: Expert-level Python, C++, and familiarity with functional programming paradigms.
- Visionary Mindset: Ability to think conceptually about AGI timelines and system scalability.