Senior Machine Learning Operations Engineer

Who you are

• 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
• 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

What the job involves

• 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

The application process

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