Job Description
We are on a mission to redefine the boundaries of human potential through next-generation computing. Nexus Future Labs is seeking a visionary Senior AI & Quantum Strategy Architect to lead our research division into 2026 and beyond. In this pivotal role, you will bridge the gap between theoretical physics, advanced machine learning, and commercial application, driving innovations that will power the global economy of tomorrow.
As a key strategist within our elite R&D team, you will define the technical vision for our quantum supremacy projects, ensuring our AI models are robust, scalable, and ethically aligned. You will collaborate with top-tier engineers, data scientists, and industry thought leaders to build a future-proof technological stack.
Why join us?
- Work on cutting-edge projects that define the future of technology.
- Competitive compensation and equity packages.
- Flexible remote-first policy with a premium office in downtown SF.
Responsibilities
- Define and execute the long-term research roadmap for AI and Quantum Computing integration, focusing on 2026 capabilities.
- Lead cross-functional teams in the design and architecture of scalable machine learning systems and quantum algorithms.
- Identify emerging technologies and market trends to drive innovation and competitive advantage.
- Mentor junior architects and data scientists, fostering a culture of continuous learning and technical excellence.
- Communicate complex technical concepts to non-technical stakeholders and executive leadership.
- Oversee the ethical implications of AI deployment, ensuring compliance with global regulations.
Qualifications
- 10+ years of experience in software engineering, data science, or theoretical physics, with at least 5 years in a strategic or architectural leadership role.
- Advanced degree (PhD preferred) in Computer Science, Physics, Mathematics, or a related technical field.
- Deep understanding of quantum computing concepts (e.g., Qubits, Superposition, Entanglement) and their application to optimization problems.
- Expertise in Python, TensorFlow, PyTorch, or equivalent machine learning frameworks.
- Proven track record of leading high-impact R&D initiatives from conception to deployment.
- Strong analytical skills with the ability to solve complex, ambiguous problems.