About Quandela

Quandela is a European deeptech company building modular, scalable and energy-efficient spin-photonic quantum computers. We develop the full quantum computing stack, from semiconductor quantum emitters and photonic processors to control systems, software and applications. Our platforms are available through the cloud and as on-premises systems. Our ambition is to build fault-tolerant quantum computers capable of solving problems beyond the reach of classical computation.

The role

We are looking for an AI Scientist to join Quandela's AI and Quantum Machine Learning team between Paris and Montreal. You will develop and evaluate machine-learning approaches for quantum computing, covering both: AI for quantum systems, including calibration, control, decoding for quantum error correction; quantum and hybrid machine learning, including rigorous comparisons with state-of-the-art classical methods, using MerLin, Quandela's framework for quantum machine learning. You will work on research with colleagues across AI, quantum algorithms, software, product and hardware. The Montreal team is a central part of Quandela's AI activities. This role therefore offers significant ownership and the opportunity to help shape and grow the team over time.

What You'll Do

Design, implement and train machine-learning and quantum machine-learning models. Develop AI methods to improve the calibration, control and performance of quantum systems. Benchmark classical, quantum and hybrid methods using meaningful baselines and evaluation metrics. Contribute actively to the development of the MerLin framework. Contribute to publications and collaborations with academic partners, including the Montreal research ecosystem. Present your work internally and at scientific conferences and technical events. Help define Quandela's future AI research directions and mentor junior researchers as the team grows

Requirements

What we are looking for

We are looking for an AI scientist, or an experienced industry practitioner with an equivalent background, who is eager to apply state-of-the-art classical machine-learning methods to scientific and engineering challenges in quantum computing. The role is primarily focused on using AI to improve quantum technologies, while also providing opportunities to develop and investigate quantum and hybrid machine-learning models. PhD + 3 years of experience or equivalent industrial R&D experience in machine learning. Strong foundations in modern machine learning, experimental methodology and model evaluation. Excellent scientific programming skills, particularly in Python and common machine-learning frameworks. Experience taking research ideas from initial exploration to robust implementation. Interest in working on both longer term research and concrete product problems. Strong communication skills and the ability to work autonomously within a focused, multidisciplinary team. Professional fluency in English.

Bonus Points

Previous experience applying AI to physical systems, scientific computing, hardware control or experimental data. Knowledge of quantum computing, quantum machine learning or photonic quantum technologies. Experience mentoring junior researchers or helping define technical research directions

Benefits

Location

Montreal Office - Mila, Quebec AI Institute, 6666 Rue Saint-Urbain, QC H2S 3H1 (4th floor).

What we offer

20 days of paid annual leave per year, plus office closure during the end-of-year holidays (not deducted from your balance) Comprehensive group insurance: health, dental, life and disability coverage (individual or family), effective after 3 months.Health & dental care with no deductible, including prescription drugs, vision care and up to $1,000/year of dental Generous paramedical coverage: $500/year per practitioner and Free virtual healthcare (telemedicine) and a 24/7 nurse info line Group RRSP through payroll, with employer matching up to 4% of your salary, plus the usual tax advantages Contributions to the Régime de rentes du Québec (RRQ), split between employer and employee.