Job Description
Join the forefront of technological evolution at QuantumLeap Dynamics, where we're engineering the computational landscape of 2026 and beyond. We seek a visionary Quantum Algorithm Engineer to architect the next generation of quantum solutions that will redefine industries. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical breakthroughs into real-world applications. This role combines deep quantum physics expertise with cutting-edge machine learning to solve previously unsolvable problems in cryptography, optimization, and AI. Collaborate with Nobel laureates and pioneer the algorithms that will power humanity's technological leap forward.
Why QuantumLeap?
- Cutting-edge quantum hardware access
- Equity package and industry-leading benefits
- Collaborative research environment with 24/7 lab access
- Annual innovation retreats and conference sponsorships
Responsibilities
- Design and implement novel quantum algorithms for NISQ-era and fault-tolerant systems
- Optimize quantum circuits for real-world hardware constraints using error mitigation techniques
- Develop hybrid quantum-classical machine learning frameworks for 2026-scale data processing
- Lead cross-functional research teams in prototyping quantum solutions for finance and biotech
- Translate complex quantum problems into deployable software solutions using Python and Qiskit
- Publish breakthrough research in top-tier journals and conferences
- Mentor junior researchers and contribute to open-source quantum computing initiatives
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science (or equivalent industry experience)
- Expertise in quantum circuit design, quantum error correction, and variational algorithms
- Proficiency with quantum programming frameworks (Qiskit, Cirq, PennyLane) and Python
- Published research in quantum machine learning or quantum optimization
- Demonstrated ability to translate theoretical concepts into practical implementations
- Experience with high-performance computing and parallel processing architectures
- Strong background in linear algebra, probability, and information theory