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're a diverse team of 250+ brilliant minds from over 35 countries united by a single goal: to revolutionise computing with a practical fault-tolerant quantum machine. Are you ready to take on unprecedented challenges and contribute to revolutionising technology? Join us, and let's shape the future of quantum computing together!

**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 **Senior Machine Learning Engineer** , you will own the architectural blueprint and technical direction of key components in our ML stack. This is a high-autonomy role where you'll set the standards for how we build, scale, and deploy.

**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.
* **Technical Roadmap:** Identify gaps in the ML stack and proactively propose, scope, and prioritize multi-quarter improvements. You will own the roadmap for one or more core optimization components.
* **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.
* **Engineering Influence**: Contribute to engineering standards beyond the immediate team. Participate in cross-team design reviews, define reusable patterns, and help shape how ML is built across the organization.

**Requirements**

* 5+ years of industry experience in Machine Learning Engineering or Software Engineering with a strong ML focus, or a PhD + 3 years in the industry.
* **Ownership Track Record**: Demonstrated experience independently owning an ML project end-to-end, from ambiguous problem definition through production deployment and iteration.
* **Technical Proficiency:** Advanced expertise in Python and the modern ML stack (PyTorch/JAX). Proven experience 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.
* **Research Impact:** Lead authorship at top-tier ML conferences, or a background in Physics/Quantum mechanics.

**Recruitment Process**

* Screening Call with Grace, Talent Acquisition Specialist (30 min)
* Hiring Manager Interview with Etienne (45 min)
* Technical Interview with the Team (90 min)
* Leadership Team Interview (30 min)
* Fit Interview (45 min)
* Reference Check

**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 P**arental 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