Job Description
Join Nexus Quantum Solutions at the forefront of 2026's technological revolution as a Quantum Machine Learning Engineer. We're pioneering the next generation of AI systems that leverage quantum computing to solve previously unsolvable problems. In this role, you'll architect hybrid quantum-classical models, optimize quantum algorithms for real-world applications, and collaborate with Nobel laureates in our state-of-the-art R&D facility. Your work will directly impact industries from drug discovery to climate modeling, pushing the boundaries of computational science.
We offer competitive equity packages, unlimited learning stipends, and the opportunity to shape the future of quantum AI. Our culture celebrates intellectual curiosity and rewards bold innovation.
Responsibilities
- Design and implement hybrid quantum-classical machine learning frameworks
- Develop quantum algorithms for optimization and pattern recognition tasks
- Collaborate with hardware teams to optimize quantum circuit performance
- Create scalable quantum data pipelines and quantum neural network architectures
- Lead research initiatives in quantum error correction and fault tolerance
- Mentor junior engineers in quantum programming best practices
- Publish findings in leading scientific journals and industry conferences
Qualifications
- PhD in Quantum Computing, Computer Science, or related field (or equivalent experience)
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
- Expertise in machine learning frameworks (PyTorch, TensorFlow) and Python
- Deep understanding of quantum mechanics principles and quantum algorithms
- 3+ years of experience in high-performance computing environments
- Published research in quantum machine learning or quantum information theory
- Strong problem-solving skills for complex multi-variable optimization challenges