Job Description
We are looking for a visionary Lead AI Architect to build the infrastructure that defines the year 2026. At Chronos AI, we are not just predicting the future; we are architecting it. We are seeking a pioneer who understands the convergence of General Artificial Intelligence (AGI) and Quantum Computing to lead our core engineering division in San Francisco.
In this role, you will be at the forefront of post-silicon computing, designing neural pathways that rival human cognition. You will define the standards for ethical AI, ensuring our systems are not only powerful but responsible. If you are ready to leave your mark on the next decade of technology, we want to hear from you.
Why Join Us?
- Work on Next-Generation AI systems that will redefine human-machine interaction.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a premium office in the heart of SF.
- Access to cutting-edge hardware labs and quantum research facilities.
Responsibilities
- Architect and implement General Artificial Intelligence frameworks capable of autonomous learning and adaptation.
- Lead the integration of Quantum-Classical Hybrid Architectures to solve complex computational problems.
- Define and enforce Ethical AI Governance protocols to ensure bias-free and safe model deployment.
- Mentor and cultivate a high-performing engineering team focused on Neuromorphic Computing research.
- Optimize deep learning models for Edge Computing and real-time inference.
- Collaborate with global R&D partners to standardize Post-Silicon programming languages.
Qualifications
- Ph.D. in Computer Science, Physics, Applied Mathematics, or a related field.
- 10+ years of experience in Machine Learning, Deep Learning, and Artificial Intelligence.
- Proven expertise in Quantum Algorithms and frameworks (e.g., Qiskit, Cirq, or Google Cirq).
- Strong command of programming languages including Python, C++, and Go.
- Experience leading large-scale engineering teams through rapid product development cycles.
- Demonstrated ability to navigate the complexities of Neural Network Optimization and hardware acceleration.