Senior MLOps Engineer

Job summary

Responsibilities

We are building a modern, AI-ready Data Platform on Google Cloud Platform.

• 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.

What they're looking for

• 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.

Tech stack

• GCP
• Python
• Docker
• Kubernetes
• PyTorch
• TensorFlow
• scikit-learn