Quantum Software Engineer – Machine Learning

Role Overview

• 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
• Ability 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%
• Ph.D. in Computer Science, Physics, Applied Mathematics, or a related field (preferred)
• Research experience in quantum machine learning and/or quantum information science (preferred)
• Experience implementing variational quantum algorithms, parameterized quantum circuits, or quantum kernel methods (preferred)
• Experience developing tensor network algorithms for large-scale modeling or simulation (preferred)
• Familiarity with quantum SDKs (e.g., Qiskit, Cirq, Braket, PennyLane) (preferred)
• Strong publication record in machine learning, quantum computing, or computational physics (preferred)
• Experience working with quantum sensor data or quantum hardware calibration workflows (preferred)

Tech Stack

• Python
• PyTorch
• Tensorflow

Benefits

• 100% company-paid medical, dental, vision, short/long-term disability
• Employer-funded Health Savings Account
• Unlimited PTO
• 401(k) match
• Company-paid Life and AD&D Insurance
• Flexible Savings Account
• Paid FMLA, Maternity/Paternity Leave
• Employee Assistance Program
• Student Loan Repayment
• Equity Program