Senior MLOps Engineer

About the role

We are looking for a Senior MLOps Engineer to lead the design, build and deployment of scalable machine‑learning infrastructure for our AI‑first projects. The role is fully remote and focuses on production‑ready solutions, especially for computer‑vision applications.

Key responsibilities

• Design and implement end‑to‑end ML pipelines, from data ingestion to model training, deployment and monitoring.
• Develop and optimise CI/CD pipelines for automated model delivery.
• Containerise and orchestrate services using Docker and Kubernetes in cloud environments (AWS, GCP, SageMaker).
• Integrate computer‑vision models into production systems and maintain scalable inference services.
• Collaborate closely with data scientists and engineering teams to ensure reliable model performance.
• Monitor, troubleshoot and optimise deployed models for reliability, cost‑efficiency and latency.

Required profile

• 5+ years of hands‑on experience in MLOps or Machine Learning Engineering.
• Strong production‑level Python coding skills.
• Proven experience with Docker, Kubernetes and cloud platforms such as AWS or GCP.
• Experience building CI/CD workflows for ML and using experiment‑tracking tools (MLflow, DVC, Weights & Biases).
• Solid background in computer‑vision pipelines and model optimisation.
• Bachelor’s or Master’s degree in Computer Science, Engineering or a related field (preferred).

Required skills

• Python
• Docker
• Kubernetes
• AWS
• GCP
• SageMaker
• CI/CD pipelines
• MLflow
• DVC
• Weights & Biases
• Computer‑vision
• Model optimisation