Job Description
Join Nexus Quantum Labs at the forefront of computational revolution! We're pioneering quantum machine learning solutions that will redefine 2026's technological landscape. As a Quantum ML Engineer, you'll architect hybrid quantum-classical systems to solve previously unsolvable problems in cryptography, drug discovery, and climate modeling. Our Austin-based R&D hub offers unparalleled resources including 128-qubit processors and a team of Nobel-caliber researchers. This is your chance to shape the next era of artificial intelligence.
Responsibilities
- Design quantum neural networks leveraging Qiskit and PennyLane frameworks
- Develop error mitigation protocols for NISQ-era quantum processors
- Optimize hybrid quantum-classical pipelines for enterprise-scale ML workloads
- Collaborate with theoretical physicists to validate quantum advantage claims
- Implement fault-tolerant algorithms on superconducting quantum hardware
- Publish breakthrough research in Nature Quantum Information
- Mentor junior engineers in quantum computing best practices
Qualifications
- PhD in Quantum Computing, Physics, or ML with 3+ years industry experience
- Expertise in quantum circuit optimization and tensor network simulations
- Proficiency in Python, C++, and quantum ML libraries (Qiskit, Cirq, PennyLane)
- Demonstrated experience with variational quantum algorithms (VQE, QAOA)
- Strong background in linear algebra, quantum information theory, and topology
- Published research in quantum machine learning or related fields
- Experience with quantum cloud platforms (IBM Quantum, Amazon Braket)