Job Description
Are you ready to architect the future of humanity?
Nexus Future Industries is pioneering the The 2026 Protocol, a revolutionary initiative aimed at integrating generative AI with predictive quantum mechanics. We are seeking a visionary Lead AI Architect to define the core infrastructure that will power our solutions for the next decade.
In this high-impact role, you will not just write code; you will shape the cognitive architecture of our products. You will bridge the gap between theoretical AI research and scalable production systems.
Why Join Us?
- Work on cutting-edge technology that defines the 2026 landscape.
- Competitive compensation and equity packages.
- Flexible remote-first policy with quarterly team meetups in SF.
Join the vanguard of technological evolution.
Responsibilities
- Architect Neural Core: Design and implement scalable deep learning models and neural network architectures optimized for the 2026 computing environment.
- System Integration: Lead the integration of AI models with legacy systems and emerging quantum interfaces.
- Research & Development: Stay at the forefront of AI trends, specifically focusing on Large Language Models (LLMs) and reinforcement learning.
- Team Leadership: Mentor a team of junior data scientists and engineers, fostering a culture of innovation and continuous learning.
- Performance Optimization: Drive the optimization of inference speeds and reduce computational costs for large-scale deployments.
- Prototyping: Rapidly prototype new AI concepts to validate feasibility before full-scale rollout.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of professional experience in AI/ML engineering, with at least 3 years in a lead or architectural role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (Kubernetes, Spark).
- Domain Knowledge: Strong understanding of natural language processing, computer vision, or predictive analytics.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for diverse stakeholders.
- Innovation: A track record of introducing novel algorithms or significantly improving existing systems.