Senior MLOps Engineer

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.

• 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.

• 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.