Job Description
We are on the precipice of a new era. As we look toward 2026, the boundaries between human cognition and machine intelligence are dissolving. Nexus Future Labs is seeking a visionary Senior AI Architect to lead our core research division, building the autonomous systems and long-horizon reasoning models that will define the next decade of technology.
In this role, you won't just be writing code; you will be architecting the brain of tomorrow. You will work at the intersection of Deep Learning, Cognitive Science, and Robotics, pushing the envelope of what's possible in Generative AI and Agentic Workflows.
Why join us?
- Work with a team of Nobel laureates and industry pioneers.
- Access to cutting-edge GPU clusters and quantum computing resources.
- Competitive equity package for long-term impact.
- Flexible remote-first culture with quarterly in-person innovation sprints.
If you are ready to build the future, we want to hear from you.
Responsibilities
- Architect Next-Gen Neural Systems: Design and deploy scalable, self-improving deep learning architectures capable of handling long-horizon tasks and complex reasoning.
- Lead Agentic AI Development: Spearhead the development of autonomous AI agents that can plan, execute, and learn from multi-step workflows in real-time.
- Ethical AI Governance: Establish and enforce rigorous safety protocols and alignment strategies to ensure AI systems remain beneficial and unbiased.
- Optimize Inference Efficiency: Reduce model latency and energy consumption for deployment on edge devices and massive distributed clusters.
- Cross-Functional Leadership: Collaborate with quantum computing researchers and data scientists to integrate hybrid classical-quantum algorithms.
- Roadmap Strategy: Define the technical roadmap for AI capabilities, anticipating industry shifts towards 2026 and beyond.
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 professional experience in Deep Learning, with a proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR).
- Technical Skills: Proficiency in Python, PyTorch, or JAX; extensive experience with Large Language Models (LLMs) and Transformers.
- Mathematical Fluency: Strong grasp of linear algebra, calculus, probability theory, and optimization techniques.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts to non-technical stakeholders.
- Passion: Deep curiosity about the future of AI and a commitment to ethical technological advancement.