Alice & Bob is developing the first universal, fault-tolerant quantum computer to solve the world’s hardest problems.
The quantum computer we envision building is based on a new kind of superconducting qubit: the Schrödinger cat qubit. In comparison to other superconducting platforms, cat qubits have the astonishing ability to implement quantum error correction autonomously!
We are at the forefront of the quantum race, competing with tech giants such as Google or IBM, and we are growing fast after securing €100 million of funding in 2025 to develop our unique technology.
Currently 100+ and counting, between physicists, PhD students, engineers and experienced business professionals, we are united to reach our ambitious goal. Are you a quantum pioneer? Join us on a mission to reshape the future!
About the role:
The Performance Optimization team is at the heart of our mission: using Machine Learning to dramatically improve the quality, speed, and reliability of the quantum chip lifecycle.
As a Machine Learning Engineer, you will take ownership of critical components in our machine learning stack and move beyond individual task execution to driving the architecture and reliability of our ML pipelines.
As a technical partner to physicists, you will help to convert ambiguous research goals into concrete, scalable software specifications. Additionally, you will be a standard-bearer for software excellence, mentoring junior engineers and helping bridge the gap between our experimental research and robust, production-grade platform tooling.
Responsibilities
- Architecture & Deployment: Lead the design and implementation of complex ML workflows. You will architect solutions that are not just accurate, but scalable, maintainable, and observable in production.
- Cross-Functional Leadership: Proactively collaborate with quantum physicists to identify bottlenecks in the chip lifecycle. You will translate high-level physical constraints into precise algorithmic requirements and drive the solution to completion.
- Production Rigor: Ensure high availability and robustness of the optimization stack. You will champion best practices in testing, CI/CD, and versioning for machine learning models.
- MLOps & Infrastructure: Optimize our training pipelines on GPU clusters. You will identify inefficiencies in job scheduling or data loading and implement systemic fixes to reduce turnaround time for experiments.
- Mentorship & Standards: Conduct code reviews and guide junior engineers in software design patterns. You will play a key role in defining the "gold standard" for engineering within the optimization team.
Requirements
- Experience: 3+ years of industry experience in Machine Learning Engineering or Software Engineering with a strong ML focus, or PhD.
- Technical Proficiency: Advanced expertise in Python and the modern ML stack (PyTorch/JAX). Proven experience in building and maintaining production-grade software (not just notebooks).
- System Knowledge: Experience with MLOps tools, distributed training, or cloud infrastructure.
- Mathematical Fluency: Strong grasp of linear algebra and optimization with the ability to discuss technical trade-offs with research scientists.
Nice to Have
- Deep Tech Experience: Experience working in hardware-constrained environments (robotics, semiconductors, physics) or with scientific computing.
- Track Record: Demonstrable history of taking an ML project from a vague concept to successful deployment in a user-facing or critical path system.
- Research Impact: Lead authorship at top-tier ML conferences, or a background in Physics/Quantum mechanics.
Benefits
- Our success is your success: own it with our BSPCE plan
- Direct IP Compensation: Earn substantial bonuses for driving the core patents that define our quantum architecture.
- Flexible remote policy, up to 40 % a month
- A Parental Plan including additional benefits such as crèche support or additional days-off to take care of under 12 years old children
- Subsidized membership with Urban Sports Club
- Mental health support with moka.care
- 25-day vacation policy (as per French law) + RTT
- Half of transportation cost coverage (as per French law), or yearly allowance for the die-hard bicycle users
- Competitive health coverage with Alan
- Meal vouchers with Swile, as well as access to a fully equipped and regularly stocked kitchen
- French language courses covered by the company for those interested
Recruitment Process
- Screening Call with Grace, Talent Acquisition Specialist (30 min)
- Hiring Manager Interview with Etienne, Senior Manager, Performance Optimisation (45 min)
- Technical Interview/Presentation with the Team (90 min)
- Leadership/Fit Interview (45 min)
- Reference check
Research shows that women might feel hesitant to apply for this job if they don't match 100% of the job requirements listed. This list is a guide, and we'd love to receive your application even if you think you're only a partial match. We are looking to build teams that innovate, not just tick boxes on a job spec.
You will join of one of the most innovative startups in France at an early stage, to be part of a passionate and friendly team on its mission to build the first universal quantum computer!
We love to share and learn from one another, so you will be certain to innovate, develop new ideas, and have the space to grow.
