We are seeking a highly skilled
MLOps Engineer with Google Cloud Platform specialization to design, implement, and manage scalable machine learning infrastructure on Google Cloud Platform (Google Cloud Platform). This role will bridge the gap between Data Science, Data Engineering, and DevOps teams to enable seamless model development, deployment, and monitoring in production environments.
The ideal candidate will have deep expertise in Google Cloud Platform services, strong programming skills, and hands-on experience building end-to-end MLOps pipelines.
Required Qualifications
Technical Skills
- 5+ years of experience in MLOps / Machine Learning Engineering
- Strong programming skills in Python
- Hands-on expertise with Google Cloud Platform services:
- Vertex AI
- GKE
- Cloud Run
- BigQuery
- Cloud Storage
- Cloud Composer
- Experience with Docker & Kubernetes
- Experience with CI/CD pipelines (GitLab, Bitbucket)
- Experience with Terraform (IaC)
- Knowledge of ML frameworks:
- TensorFlow
- PyTorch
- Scikit-learn
- Strong understanding of:
- Data pipelines (ETL/ELT)
- BigQuery, Dataflow, Dataproc (PySpark)
Preferred Qualifications
- Experience with:
- Vertex AI Pipelines / Kubeflow on GKE
- Feature Store implementation
- Exposure to Generative AI & RAG architectures
- Experience with model monitoring and drift detection
- Knowledge of microservices and API development:
- Cloud Functions
- Cloud Endpoints
- Google Cloud Certifications:
- Professional Machine Learning Engineer
- Professional Cloud Architect