Senior MLOps Engineer

Alice & Bob is hiring a Senior MLOps Engineer in Paris, France. Level rates it ; you can apply on Alice & Bob.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Vertex AI, PyTorch and TensorFlow.
Level classifies it as a senior role.
Level lists 50 other open roles at Alice & Bob.

AI in this role

Vertex AIPyTorchTensorFlowscikit-learn

ml-ops

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
We are building a modern, AI-ready Data Platform on Google Cloud Platform.
As a Senior MLOps / LLMOps Engineer, you will help turn ML and AI experiments into reliable, production-ready solutions. You will work closely with researchers, data scientists and engineers to build the infrastructure and practices needed to train, deploy and operate models at scale.
You will also play an important role in helping teams adopt AI technologies and best practices across the company.

Responsibilities

Build and maintain MLOps / LLMOps infrastructure on GCP, including ML pipelines, model deployment and monitoring.
Help researchers and data scientists bring models from experimentation to production.
Design reliable and scalable solutions for both traditional ML and GenAI / LLM use cases.
Ensure models and experiments are reproducible, observable and maintainable.
Advise teams on ML/AI architecture, tooling and best practices.
Share knowledge and help teams make effective use of GCP AI services.
Work closely with Data Engineering and DevOps teams on data, infrastructure and CI/CD.
Contribute to the evolution of the ML/AI platform as the company's AI needs grow.

Requirements

7+ years of experience in ML Engineering, MLOps, Software Engineering or a related field.
Strong Python skills and experience running ML systems in production.
Solid experience with MLOps, including pipelines, deployment and monitoring.
Experience with GCP / Vertex AI is a strong plus.
Experience with Docker and Kubernetes/GKE.
Familiarity with modern ML frameworks such as PyTorch, TensorFlow or scikit-learn.
Experience with LLMs / GenAI.
Strong analytical and communication skills, with the ability to work with both technical and research teams.
Fluent in English.

Recruitment Process

Screening call with Doriane (30 min)
Hiring Manager interview (45 min)
Technical onsite Interview - (90min)
Leadership Interview (30 min)
Fit Interview (30 min)

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 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.

How we rate this

Senior MLOps Engineer at Alice & Bob rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior MLOps Engineer is an open job at Alice & Bob.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Paris.
The job was posted on August 18, 2026.
Seniority: senior.
Applications are handled by Alice & Bob. Apply on Alice & Bob

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsVertex AIPyTorchTensorFlowscikit-learn

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through how you've used Vertex AI in your day-to-day work.
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ML Ops, Vertex AI, PyTorch, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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