MLOps Engineer
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About the Role
Role name MLOps Engineer
Location - Mississauga 2 or 3 days hybrid
Duration - Contract
Exp Level - 7+ years
Role Descriptions:
Essential Skills: Expertise in cloud platforms| ML engineering| data pipelines| and CICD for deploying and managing machine learning solutions.
Skill required
1.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
2.ML Data EngineeringoUnderstanding 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 pysparkScala using serverless dataproc
3.CICD for ML (MLOps)knowledge of CICD tools Looper proJenkins. Model versioning| continuous training| and deployment using Vertex AI pipelines.
4.Automation Scripting. Strong programming skills in Python| Bash| and SQL automation of workflows and ML pipelines.
5.DevOps Containerization Kubernetes (GKE) and Docker for containerization and orchestration. Good to have Helm charts and YAML for Kubernetes deployments.
6.Monitoring Observability Cloud Monitoring| Cloud Logging| Prometheus| and Grafana for monitoring and alerting. Model performance monitoring with Vertex AI Model Monitoring.
7.Security Compliance Understanding of VPC| firewall rules| and service accounts. Managing secrets using Secret Manager.
8.Data Science Must understand general data science methods and the development life cycleAn ML Ops Engineer responsible for building| automating| and managing scalable machine learning pipelines and deployments on Google Cloud Platform.
Regards,
Email: ana@apptoza.com
Phone #: 6788247770
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