Job Description
Join the forefront of technological revolution at Nexus Quantum Solutions, where we're pioneering the next generation of AI-powered quantum systems. As a Quantum Machine Learning Engineer, you'll architect and deploy groundbreaking algorithms that merge quantum computing with artificial intelligence to solve humanity's most complex challenges. Our state-of-the-art lab in San Francisco offers unparalleled resources to accelerate your research and development.
We're seeking visionary innovators to push the boundaries of computational possibility. You'll collaborate with Nobel Prize-winning physicists and elite AI researchers to create scalable quantum neural networks, optimize quantum machine learning pipelines, and develop hybrid quantum-classical frameworks that redefine industry standards.
Responsibilities
- Design and implement quantum machine learning algorithms leveraging qubit-based neural networks
- Develop hybrid quantum-classical models for predictive analytics and optimization
- Optimize quantum circuit performance for real-world ML workloads
- Create fault-tolerant quantum error correction systems for ML applications
- Lead research on quantum-enhanced deep learning architectures
- Collaborate with cross-functional teams to integrate quantum solutions into production systems
- Publish breakthrough research in top-tier quantum computing journals
Qualifications
- PhD in Quantum Computing, Machine Learning, or related field (MS with exceptional experience considered)
- Proficiency in quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Expertise in Python, TensorFlow/PyTorch, and high-performance computing
- Strong background in quantum information theory and quantum algorithms
- Experience with cloud quantum computing platforms (AWS Braket, IBM Quantum)
- Proven track record of publishing quantum ML research or developing production systems
- Deep understanding of quantum error correction and fault-tolerant computing