Job Description
Join NexaQuantum at the forefront of technological innovation as a Quantum Machine Learning Engineer in 2026. We're pioneering the convergence of quantum computing and AI to solve humanity's most complex challenges. As a visionary on our R&D team, you'll architect next-generation quantum algorithms that redefine machine learning capabilities, working with cutting-edge quantum hardware and neural network architectures.
This role offers unparalleled opportunity to shape the future of computational intelligence in a collaborative environment where Nobel-caliber researchers and industry disruptors unite. You'll contribute to breakthrough projects in quantum cryptography, optimization, and generative AI that will transform industries from healthcare to climate modeling.
Responsibilities
- Design and implement hybrid quantum-classical machine learning algorithms for real-world applications
- Develop quantum neural networks leveraging Qiskit, PennyLane, and emerging quantum processors
- Optimize quantum circuits for ML workloads achieving quantum advantage in benchmark tests
- Create robust error mitigation strategies for quantum ML systems operating near fault-tolerance
- Collaborate with quantum hardware teams to co-design qubit architectures optimized for ML operations
- Pioneer novel approaches to quantum data encoding and feature extraction in high-dimensional spaces
- Lead open-source initiatives advancing quantum ML frameworks and industry standards
Qualifications
- PhD in Quantum Computing, Machine Learning, or related field with 3+ years industry experience
- Expertise in quantum programming languages (Q#, Qiskit, Cirq) and quantum circuit optimization
- Deep understanding of quantum algorithms (VQE, QAOA, HHL) and their ML applications
- Proven track record developing production ML systems with TensorFlow/PyTorch
- Experience with quantum error correction and fault-tolerant computing architectures
- Strong background in linear algebra, probability theory, and computational complexity
- Publication record in top-tier quantum computing or ML conferences (e.g., QIP, NeurIPS)