Requirements

- Expertise in cloud platforms, ML engineering, data pipelines and CI/CD for deploying and managing machine learning solutions.

- Google Cloud Platform (GCP) services: AI Platform (Vertex AI), Cloud Storage, BigQuery, Cloud Functions, Cloud PubSub, Cloud Build, Airflow, and Cloud Run.

- Understanding of ML concepts and LLMs (training, validation, hyperparameter tuning, evaluation).

- Experience with TensorFlow, Keras, PyTorch, and scikit-learn.

- Data preprocessing, ETL, and data pipelines using PySpark and Scala using serverless dataproc.

CI/CD for ML (MLOps)

- Knowledge of CI/CD tools like Looper Pro and Jenkins.

- Model versioning, continuous training, and deployment using Vertex AI pipelines.

Automation Scripting

- Solid programming skills in Python, Bash, and SQL.

- Automation of workflows and ML pipelines.

DevOps Containerization





- Kubernetes (GKE) and Docker for containerization and orchestration.

- Good to have Helm charts and YAML for Kubernetes deployments.

Monitoring Observability

- Cloud Monitoring, Cloud Logging, Prometheus and Grafana for monitoring and alerting.

- Model performance monitoring with Vertex AI Model Monitoring.

Security Compliance

- Understanding of VPC, firewall rules, and service accounts.

Data Science

- Must understand general data science methods and the development life cycle.

An MLOps Engineer responsible for building, automating, and managing scalable machine learning pipelines and deployments on Google Cloud Platform.

📌 ML Platform Engineer - Google Cloud (GCP) and Vertex AI (Mississauga)
🏢 Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
📍 Mississauga