Desirable Skills:
· Google Cloud
· Azure Machine Learning (ML)
Role Requirements:
· Expertise in cloud platforms, ML engineering, data pipelines and CI/CD for deploying and managing machine learning solutions.
Cloud Platforms Services (Google Cloud)
· Google Cloud Platform (GCP) services: AI Platform (Vertex AI), Cloud Storage, BigQuery, Cloud Functions, Cloud PubSub, Cloud Build, Airflow, and Cloud Run.
· Element Platform visibility
ML Data Engineering
· 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
· Strong 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.
· Managing secrets using Secret Manager.
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.
Experience Required: 6-8
MLPlatform Engineer – Google Cloud (GCP) and Vertex AI • Mississauga, ON, ON, ca
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