Senior Research Engineer developing mechanical designs for engine demonstrators at GKN Aerospace. Leading technology integration and collaborating across engineering disciplines in aeronautics.
About the role
- Research Engineer at Quantiphi implementing quantum-assisted hybrid algorithms for optimization and machine learning. Collaborating with teams to develop scalable industry solutions with a focus on quantum computing technologies.
Responsibilities
- Design and implement quantum-assisted hybrid algorithms for optimization, simulation, machine learning, and generative modeling across real-world industry use cases
- Develop, debug, and optimize quantum workloads while applying techniques across different hardware and frameworks
- Improve existing algorithm efficiency through transpilation, circuit depth reduction, Hamiltonian formulation, shot optimization, and error correction strategies
- Collaborate with interdisciplinary teams to translate quantum research into practical, scalable solutions aligned with industry needs
- Contribute to intellectual property and thought leadership through patents, publications, and technical content
- Mentor junior researchers and engineers while fostering collaborative brainstorming and sharing perspectives on technical best practices
Requirements
- Bachelor/Master’s degree with 3+ years of industry experience or PhD in Quantum Computing, Physics, Chemistry, Computer Science, Electrical Engineering, or a related field
- Strong hands-on experience with quantum programming frameworks (e.g., Qiskit, Cirq, PennyLane) and hybrid quantum–classical systems
- Demonstrated experience working with real quantum hardware and platforms (e.g., IBM Quantum, AWS Braket, Google Quantum, or related hardware) and familiarity with superconducting qubits, trapped ions, and neutral atoms
- Solid understanding of quantum algorithms, quantum machine learning, and classical machine learning techniques (deep learning, optimization, reinforcement learning, generative models)
- Experience with transpilation, circuit optimization, error correction, and performance evaluation on noisy quantum devices
- Domain knowledge in at least one industry (e.g., finance, healthcare, materials, manufacturing, or logistics)
- Proven ability to translate research concepts into practical, industry-relevant solutions, with a demonstrated track record of patents, peer-reviewed publications, or equivalent applied research outputs
- Experience with managing/mentoring junior engineers, including conducting code and design architecture reviews following best practices
Benefits
- Ample opportunities to learn and grow
- Interact with colleagues from varied experience and backgrounds around the globe
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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