Job Description
Join Nexus Quantum Technologies at the forefront of 2026's technological revolution. We're pioneering quantum machine learning applications that will redefine industries, and we need visionary engineers to architect the future. This role offers unparalleled opportunities to work with cutting-edge quantum hardware, develop hybrid AI models, and contribute to breakthroughs in computational efficiency.
Our San Francisco lab operates at the intersection of quantum physics and artificial intelligence, offering a collaborative environment where your innovations will directly impact real-world applications—from drug discovery to climate modeling. We provide comprehensive benefits including equity, flexible work arrangements, and dedicated R&D budgets.
Responsibilities
- Design and implement quantum machine learning algorithms for 2026-era computational challenges
- Develop hybrid quantum-classical AI models leveraging next-gen quantum processors
- Collaborate with physicists to optimize quantum circuit performance for ML workloads
- Lead research on quantum neural networks and quantum-enhanced data processing
- Translate complex quantum computing concepts into practical enterprise solutions
- Author technical whitepapers and contribute to open-source quantum ML frameworks
- Mentor junior engineers in quantum programming best practices
Qualifications
- PhD in Computer Science, Physics, or related field with quantum computing focus
- 3+ years experience in machine learning and deep learning frameworks
- Proficiency in quantum programming languages (Qiskit, Cirq, or Q#)
- Strong Python/C++ skills with high-performance computing experience
- Publication record in quantum machine learning or related fields
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and error correction
- Familiarity with tensor networks and quantum simulation techniques
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)