Job Description
Join FutureTech Innovations at the forefront of technological evolution as we pioneer the next generation of AI systems. We seek a visionary Quantum Machine Learning Engineer to architect and deploy quantum-powered algorithms that will redefine computational boundaries. This role offers unparalleled opportunity to shape the future of artificial intelligence while working with cutting-edge quantum hardware and advanced ML frameworks.
Our multidisciplinary team operates at the intersection of quantum physics, deep learning, and high-performance computing. You'll collaborate with Nobel laureates and industry disruptors to solve previously unsolvable problems in drug discovery, climate modeling, and autonomous systems. We provide competitive equity packages, flexible hybrid work arrangements, and access to our state-of-the-art Quantum Research Lab.
Responsibilities
- Design and implement hybrid quantum-classical machine learning models using frameworks like Qiskit and TensorFlow Quantum
- Develop quantum neural networks for optimization problems with 1000+ qubit scalability
- Create fault-tolerant quantum algorithms for real-world industrial applications
- Optimize quantum circuits for current NISQ devices and future fault-tolerant systems
- Lead cross-functional teams in translating quantum ML prototypes into production-ready solutions
- Conduct research on novel quantum computing architectures and their ML implications
- Author technical whitepapers and contribute to open-source quantum ML libraries
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 design
- Proficiency in classical ML frameworks (PyTorch, TensorFlow) and high-performance computing
- Published research in quantum machine learning or quantum algorithms
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Strong background in linear algebra, quantum mechanics, and information theory
- Track record of deploying ML models at scale in cloud environments (AWS, Azure, GCP)