Job Description
Join Nexus Future Labs at the forefront of technological evolution as we pioneer the next generation of quantum-powered machine learning systems. This role offers a rare opportunity to shape the future of AI by developing hybrid quantum-classical algorithms that solve previously impossible computational challenges. You'll work in our state-of-the-art facility collaborating with Nobel Prize-winning physicists and industry-renowned AI researchers to build the infrastructure for 2026's most disruptive technologies.
We're seeking a visionary engineer to bridge quantum computing and neural networks, creating breakthrough applications in drug discovery, climate modeling, and cryptographic security. Your innovations will directly impact how humanity solves its most complex problems.
Responsibilities
- Develop novel quantum neural network architectures leveraging Qiskit and Cirq frameworks
- Design hybrid quantum-classical optimization algorithms for enterprise-scale ML models
- Implement error mitigation techniques for NISQ-era quantum processors
- Create quantum data preprocessing pipelines for large-scale datasets
- Collaborate with hardware teams to co-design quantum accelerators
- Lead open-source contributions to quantum ML libraries
- Publish research in top-tier quantum computing conferences
Qualifications
- PhD in Quantum Computing, Machine Learning, or Physics with 3+ years industry experience
- Expertise in quantum circuit design and quantum algorithm development
- Proficiency in Python, TensorFlow/PyTorch, and quantum programming frameworks
- Deep understanding of quantum error correction and fault tolerance
- Strong background in linear algebra, probability theory, and statistical modeling
- Published research in quantum machine learning or related fields
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)