Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer the convergence of quantum computing and artificial intelligence. We seek a visionary Quantum Machine Learning Engineer to architect next-generation algorithms that will redefine computational boundaries in 2026 and beyond. This role offers unparalleled opportunities to work with bleeding-edge quantum hardware and develop transformative AI solutions.
Our state-of-the-art facility in San Francisco provides an environment where innovation thrives. You'll collaborate with Nobel laureates and industry pioneers to solve humanity's most complex challenges—from drug discovery to climate modeling. We offer competitive equity packages, flexible work arrangements, and dedicated research budgets to fuel your breakthrough ideas.
Responsibilities
- Design and implement quantum-enhanced machine learning algorithms for practical applications
- Develop hybrid quantum-classical computing frameworks for enterprise-scale AI solutions
- Optimize quantum circuits for NISQ-era hardware constraints
- Lead cross-functional R&D initiatives with physics and AI research teams
- Translate theoretical quantum computing concepts into deployable software solutions
- Contribute to open-source quantum ML libraries and frameworks
- Publish breakthrough research in top-tier scientific journals and conferences
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics (or equivalent experience)
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum circuit design
- Proven track record developing production-level ML systems using Python, TensorFlow, or PyTorch
- Deep understanding of quantum algorithms and quantum information theory
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)
- Strong background in linear algebra, probability, and statistical modeling
- Published research in quantum machine learning or related fields