Job Description
Join 2026 Technologies at the forefront of technological evolution as we pioneer quantum-AI integration for next-generation computing systems. We're seeking visionary researchers to develop algorithms that will redefine computational capabilities by 2026. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical concepts into breakthrough applications.
As a key member of our Future Systems Division, you'll collaborate with Nobel laureates and industry disruptors to solve humanity's most complex challenges. This role offers competitive equity packages, flexible research budgets, and opportunities to publish in top-tier scientific journals.
Responsibilities
- Design and implement quantum machine learning algorithms for optimization problems
- Develop hybrid quantum-classical computing architectures for real-world applications
- Lead cross-functional teams in prototyping quantum neural networks
- Secure federal and private research grants totaling $1M+ annually
- Publish breakthrough findings in Nature/Science journals
- Mentor PhD candidates in quantum information science
- Advise C-suite on ethical implications of quantum-AI convergence
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science (required)
- 3+ years experience with quantum frameworks (Qiskit, Cirq, or similar)
- Published research in quantum machine learning or error correction
- Expertise in tensor networks and quantum circuit optimization
- Proficiency in Python/C++ with quantum simulation libraries
- Demonstrated ability to secure NSF or DOE grants
- Strong background in topological quantum computing theory