Machine Learning Engineer
Boston, MA · On-site
Quantum Machines is a global leader in quantum computing control systems, and they are seeking a Machine Learning Engineer to design, build, and deploy machine learning systems for quantum processors.
Quantum Machines
1 job near Columbus, OH
Machine Learning Engineer
Boston, MA · On-site
Quantum Machines is a global leader in quantum computing control systems, and they are seeking a Machine Learning Engineer to design, build, and deploy machine learning systems for quantum processors.
Full-time
Posted 14 days ago
Job description
Job Summary:
Quantum Machines is a global leader in quantum computing control systems, and they are seeking a Machine Learning Engineer to design, build, and deploy machine learning systems for quantum processors. The role involves developing ML solutions that enhance the calibration, control, and operation of quantum technologies, working at the intersection of machine learning and quantum physics.
Responsibilities:
• Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
• Develop real-time parameter steering for calibration during QEC and between circuits.
• Develop and maintain agentic frameworks for autonomous system control and calibration.
• Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
• Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
• Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.
Qualifications:
Required:
• PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related field. 4+ years of relevant experience
• Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one of: deep learning, reinforcement learning, agentic AI
• Strong Python proficiency, including scientific or systems-oriented codebases
• Solid software engineering fundamentals (architecture, Git workflows, testing, code review)
• Proven track record of taking ML from prototype to deployment under real-world constraints - non-stationary data, expensive evaluations, or safety-critical action spaces. Robotics, online control, autonomous vehicles, or hardware-in-the-loop ML all transfer well
• Strong problem-solving skills and customer-focused mindset; ability to work independently and in multidisciplinary teams
• Proven software development track record and excellent technical communication skills
Preferred:
• Familiarity with quantum computing concepts - qubit calibration, randomized benchmarking, QEC, optimal control- advantage
• Experience with sim-to-real, multi-objective RL, or meta-learning- advantage
Company:
Quantum Machines is a leading provider of quantum control solutions, powering quantum-classical integration at scale with Hybrid Control. Founded in 2018, the company is headquartered in Claymont, USA, with a team of 201-500 employees. The company is currently Growth Stage.
Quantum Machines is a global leader in quantum computing control systems, and they are seeking a Machine Learning Engineer to design, build, and deploy machine learning systems for quantum processors. The role involves developing ML solutions that enhance the calibration, control, and operation of quantum technologies, working at the intersection of machine learning and quantum physics.
Responsibilities:
• Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
• Develop real-time parameter steering for calibration during QEC and between circuits.
• Develop and maintain agentic frameworks for autonomous system control and calibration.
• Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
• Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
• Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.
Qualifications:
Required:
• PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related field. 4+ years of relevant experience
• Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one of: deep learning, reinforcement learning, agentic AI
• Strong Python proficiency, including scientific or systems-oriented codebases
• Solid software engineering fundamentals (architecture, Git workflows, testing, code review)
• Proven track record of taking ML from prototype to deployment under real-world constraints - non-stationary data, expensive evaluations, or safety-critical action spaces. Robotics, online control, autonomous vehicles, or hardware-in-the-loop ML all transfer well
• Strong problem-solving skills and customer-focused mindset; ability to work independently and in multidisciplinary teams
• Proven software development track record and excellent technical communication skills
Preferred:
• Familiarity with quantum computing concepts - qubit calibration, randomized benchmarking, QEC, optimal control- advantage
• Experience with sim-to-real, multi-objective RL, or meta-learning- advantage
Company:
Quantum Machines is a leading provider of quantum control solutions, powering quantum-classical integration at scale with Hybrid Control. Founded in 2018, the company is headquartered in Claymont, USA, with a team of 201-500 employees. The company is currently Growth Stage.