Job Description
About OmniFuture Technologies
We are pioneering the next generation of artificial intelligence and quantum computing solutions. As we ramp up for our 2026 roadmap, we are looking for a visionary Lead Quantum AI Architect to lead our R&D division in San Francisco. You will be responsible for designing the algorithms that will power the world's most complex computational tasks, bridging the gap between classical AI and quantum mechanics.
Why Join Us?
- Work on cutting-edge technology for the 2026 era.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a premium office in SF.
Role Overview
In this high-impact role, you will define the technical strategy for our upcoming suite of quantum-enhanced AI products. You will collaborate with a world-class team of physicists, software engineers, and data scientists to deliver scalable, secure, and efficient systems.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable quantum AI architectures tailored for the 2026 technological landscape.
- R&D Strategy: Lead research initiatives to explore new frontiers in quantum entanglement and machine learning optimization.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Cross-Functional Collaboration: Work closely with product managers and stakeholders to translate complex technical requirements into actionable roadmaps.
- System Optimization: Continuously refine existing algorithms to improve processing speed and reduce error rates in quantum environments.
- Compliance & Security: Ensure all systems adhere to rigorous data security standards and ethical AI guidelines.
- Presentation: Present technical concepts and roadmaps to executive leadership and potential investors.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Physics, Mathematics, or a related field (or equivalent practical experience).
- Experience: Minimum of 7+ years of experience in AI/ML engineering, with at least 3 years in quantum computing or advanced simulation.
- Technical Skills: Proficiency in Python, C++, and quantum programming languages such as Qiskit, Cirq, or Q#. Strong understanding of linear algebra and stochastic processes.
- Leadership: Proven track record of leading technical teams and managing large-scale projects.
- Problem Solving: Exceptional ability to solve complex, multi-variable problems in high-pressure environments.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical details to non-technical audiences.
- Tools: Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).