MLOps Engineer (Google Cloud Platform Specialization)

Summary: We are looking for a highly skilled MLOps Engineer specializing in Google Cloud Platform to design, implement, and manage scalable machine learning infrastructure. This role will connect Data Science, Data Engineering, and DevOps teams to facilitate model development, deployment, and monitoring in production environments. The ideal candidate will possess deep expertise in Google Cloud services and hands-on experience in building end-to-end MLOps pipelines.

Key Responsibilities:

• Design, implement, and manage scalable machine learning infrastructure on Google Cloud Platform.
• Bridge the gap between Data Science, Data Engineering, and DevOps teams.
• Enable seamless model development, deployment, and monitoring in production environments.
• Build end-to-end MLOps pipelines.

Key Skills:

• 5+ years of experience in MLOps / Machine Learning Engineering.
• Strong programming skills in Python.
• Hands-on expertise with Google Cloud Platform services including Vertex AI, GKE, Cloud Run, BigQuery, Cloud Storage, and Cloud Composer.
• Experience with Docker & Kubernetes.
• Experience with CI/CD pipelines (GitLab, Bitbucket).
• Experience with Terraform (IaC).
• Knowledge of ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong understanding of data pipelines (ETL/ELT), BigQuery, Dataflow, and Dataproc (PySpark).
• Experience with Vertex AI Pipelines / Kubeflow on GKE and Feature Store implementation.
• Exposure to Generative AI & RAG architectures.
• Experience with model monitoring and drift detection.
• Knowledge of microservices and API development including Cloud Functions and Cloud Endpoints.
• Google Cloud Certifications such as Professional Machine Learning Engineer and Professional Cloud Architect.

Salary (Rate): £37.50 hourly

City: undetermined

Country: undetermined

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT