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Alice & Bob

Develops fault-tolerant quantum computer hardware

Senior MLOps Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeParis, FranceNo salary listed

About the Job

Requirements

  • At least 7 years of experience in machine learning engineering, MLOps, software engineering, or a related field.
  • Strong Python skills and experience running machine learning systems in production.
  • Experience with MLOps, including pipelines, deployment, and monitoring.
  • Experience with Docker and Kubernetes or GKE.
  • Familiarity with modern machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Experience with large language models or generative AI.
  • Strong analytical and communication skills, with the ability to work with technical and research teams.
  • Fluency in English.

Responsibilities

  • Build and maintain MLOps and LLMOps infrastructure on Google Cloud Platform, including machine learning pipelines, model deployment, and monitoring.
  • Help researchers and data scientists bring models from experimentation to production.
  • Design reliable and scalable solutions for traditional machine learning and generative AI or large language model use cases.
  • Ensure models and experiments are reproducible, observable, and maintainable.
  • Advise teams on machine learning and AI architecture, tooling, and best practices.
  • Share knowledge and help teams make effective use of Google Cloud Platform AI services.
  • Work closely with Data Engineering and DevOps teams on data, infrastructure, and continuous integration and continuous delivery.
  • Contribute to the evolution of the machine learning and AI platform as the company's AI needs grow.

Desired Qualifications

  • Experience with Google Cloud Platform or Vertex AI.

About the Company

Alice & Bob

Develops fault-tolerant quantum computer hardware

Alice & Bob builds quantum computers that use self-correcting superconducting qubits to achieve fault-tolerant quantum computing. Their machines are designed to run any quantum algorithm, helping researchers tackle hard, complex problems with fewer errors. The product combines a quantum computer chip and related hardware to support quantum computation, backed by simulations to aid design and testing. Unlike others that rely on less error-tolerant qubits, this company focuses on error-free operation through self-correcting qubits, aiming to provide researchers and organizations a reliable platform for advancing quantum algorithms and solving challenging problems. The overall goal is to expand practical quantum computing by delivering a dependable, scalable hardware system that researchers can use to explore and implement advanced quantum techniques.

Company size
201-500
Company stage
Early VC
Total funding
$162.1M
Headquarters
Paris, France
Founded
2020

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