Job Description
Are you ready to define the future of computing?
Aether Dynamics is pioneering the next generation of intelligent systems, and we are looking for a visionary Lead Quantum AI Research Scientist to join our elite R&D division in San Francisco. In this pivotal role, you will bridge the gap between cutting-edge quantum mechanics and advanced artificial intelligence to solve problems currently considered unsolvable.
We are building the infrastructure for 2026 and beyond. If you are driven by the challenge of rewriting the rules of computation and possess an insatiable curiosity for the unknown, we want to hear from you.
Why Join Us?
- Next-Gen Impact: Work on projects that will fundamentally alter the landscape of technology.
- World-Class Team: Collaborate with Nobel laureates and industry visionaries.
- Unlimited PTO & Remote Flexibility: We trust our team to manage their time effectively.
- Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits.
Responsibilities
- Lead Research Initiatives: Spearhead the design and implementation of quantum-enhanced machine learning algorithms tailored for 2026+ computational needs.
- Team Management: Mentor a high-performing team of research scientists and engineers, fostering a culture of innovation and rigorous scientific inquiry.
- Technical Strategy: Define the long-term technical roadmap for the Quantum AI division, ensuring alignment with company goals and industry standards.
- Collaboration: Work closely with software engineers and hardware architects to optimize software stacks for emerging quantum hardware.
- Publication & Thought Leadership: Author and present high-impact research papers at leading global conferences and publish in peer-reviewed journals.
Qualifications
- Education: Ph.D. in Computer Science, Quantum Physics, Applied Mathematics, or a related field.
- Experience: Minimum of 5 years of post-PhD experience in quantum computing, AI, or advanced machine learning.
- Technical Skills: Proficiency in Python, C++, and quantum software frameworks (e.g., Qiskit, Cirq, or PyQuil).
- Algorithm Expertise: Strong understanding of linear algebra, statistical mechanics, and complex optimization problems.
- Leadership: Proven track record of leading research teams and managing cross-functional projects.