Quantum Software Engineer - Machine Learning

Job Responsibilities

• Develop and implement quantum-inspired machine learning models, including tensor network–based architectures (e.g., MPS/TTN/PEPS-inspired models) for structured data analysis
• Design and evaluate quantum machine learning algorithms suitable for near-term and fault-tolerant quantum computers
• Build hybrid classical–quantum workflows integrating classical ML pipelines with quantum processors and/or quantum sensors
• Develop ML models for signal processing, state estimation, calibration, and noise mitigation in quantum sensing systems
• Collaborate with hardware and experimental teams to translate physical system characteristics into learning-based models
• Optimize models for performance, scalability, and deployment in HPC and low-SWaP environments
• Stay current with emerging research in tensor networks, quantum information science, and advanced ML architectures
• Contribute to research publications, technical reports, and conference presentations
• Provide technical mentorship and contribute to a collaborative, interdisciplinary research environment

Requirements

• BS or MS in Computer Science, Physics, Applied Mathematics, Electrical Engineering, or a closely related field
• Strong experience developing, training, and optimizing machine learning models
• Demonstrated experience with tensor networks, structured linear algebra, or physics-informed ML architectures
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow)
• Experience working in scientific computing and HPC environments leveraging GPU acceleration
• Strong mathematical foundation in linear algebra, probability, and optimization
• Able to communicate complex theoretical and experimental concepts clearly across teams and to external customers
• Demonstrated ability to work effectively in a collaborative, cross-functional, and fast-paced R&D environment
• Resourceful problem-solver with a track record of delivering research ideas into prototype or production systems
• Willingness to travel domestically and potentially internationally up to 10%